| Tsunenori Mine | Last modified date：2024.04.02 |
Associate Professor /
Advanced Software Engineering /
Department of Advanced Information Technology /
Faculty of Information Science and Electrical Engineering
Papers
| 1. | Menna Fateen, Tsunenori Mine:, In-Context Meta-Learning vs. Semantic Score-Based Similarity: A Comparative Study in Arabic Short Answer Grading, ArabicNLP 2023, 10.18653/v1/2023.arabicnlp-1.28, 350-358, 2023.arabicnlp-1.28, 2023.12, [URL]. |
| 2. | Wei Wang, Yujie Lin, Pengjie Ren, Zhumin Chen, Tsunenori Mine, Jianli Zhao, Qiang Zhao, Moyan Zhang, Xianye Ben, Yujun Li, Privacy-Preserving Sequential Recommendation with Collaborative Confusion, arXiv preprint, https://doi.org/10.48550/arXiv.2401.04423, arXiv:2401.04423 , 2024.01, Sequential recommendation has attracted a lot of attention from both academia and industry, however the privacy risks associated to gathering and transferring users' personal interaction data are often underestimated or ignored. Existing privacy-preserving studies are mainly applied to traditional collaborative filtering or matrix factorization rather than sequential recommendation. Moreover, these studies are mostly based on differential privacy or federated learning, which often leads to significant performance degradation, or has high requirements for communication. In this work, we address privacy-preserving from a different perspective. Unlike existing research, we capture collaborative signals of neighbor interaction sequences and directly inject indistinguishable items into the target sequence before the recommendation process begins, thereby increasing the perplexity of the target sequence. Even if the target interaction sequence is obtained by attackers, it is difficult to discern which ones are the actual user interaction records. To achieve this goal, we propose a CoLlaborative-cOnfusion seqUential recommenDer, namely CLOUD, which incorporates a collaborative confusion mechanism to edit the raw interaction sequences before conducting recommendation. Specifically, CLOUD first calculates the similarity between the target interaction sequence and other neighbor sequences to find similar sequences. Then, CLOUD considers the shared representation of the target sequence and similar sequences to determine the operation to be performed: keep, delete, or insert. We design a copy mechanism to make items from similar sequences have a higher probability to be inserted into the target sequence. Finally, the modified sequence is used to train the recommender and predict the next item.. |
| 3. | , [URL]. |
| 4. | LANDY RAJAONARIVO, TSUNENORI MINE, Few-shot learning-based lesser-known POI category estimation based on syntactic and semantic information, IEEE Access, 10.1109/ACCESS.2023.3327636, 141100-141111, 2023.10. |
| 5. | Shaowen Peng, Kazunari Sugiyama, Tsunenori Mine, Less is More: Removing Redundancy of Graph Convolutional Networks for Recommendation, ACM Transactions on Information Systems, https://doi.org/10.1145/3632751, 42, 3, 1-26, Article No. 85, 2023.11, [URL]. |
| 6. | Juntao Wang and Tsunenori Mine, Multi-Task Learning for Emotion Recognition in Conversation with Emotion Shift, The 37th Pacific Asia Conference on Language, Information and Computation (PACLIC 37), 257-266, 2023.12, [URL], As human-computer interaction continues to evolve, the importance of emotion recognition in conversation is becoming more apparent. For applications like chatbots to provide more human-like responses, it is essential for machines to understand the emotions embedded in conversations. Although most of the recent research has focused on extracting contextual information from conversations, the subtleties of emotion shifts (ES) within local conversations are often overlooked. However, acquiring knowledge about ES between interactions can reduce the rate of emotion recognition errors in dialogues with fluctuating emotions. As a solution for ES detection, we define ES between the same speaker as well as between different speakers using Emotion Recognition in Conversation (ERC) datasets. We propose a novel multi-task learning model, called MtlERC-ES, which identifies three tasks simultaneously: Emotion Recognition in Conversation (ERC), Emotion Shift (ES), and Sentiment Classification (SC). Our approach provides high-quality performance on the ERC task, consistently ranking among the top performers across multiple datasets. Our approach also demonstrates the effectiveness of custom ES tasks.. |
| 7. | Yuichi Ishikawa, Nao Kobayashi, Yasushi Naruse, Yugo Nakamura, Shigemi Ishida, Tsunenori Mine, and Yutaka Arakawa, Learning Cross-Modal Factors from Multimodal Physiological Signals for Emotion Recognition, the 20th Pacific Rim International Conference on Artificial Intelligence (PRICAI-2023), 2023.11, [URL]. |
| 8. | Bo Wang, Billy Dawton, Tsunenori Ishioka and Tsunenori Mine, Optimizing Answer Representation using Metric Learning for Efficient Short Answer Scoring, the 20th Pacific Rim International Conference on Artificial Intelligence (PRICAI-2023), 2023.11, [URL]. |
| 9. | Landy Rajaonarivo, Tsunenori Mine, Yutaka Arakawa , Little known POI category estimation via Syntactical Knowledge Graph generated via tweets, The 18th International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2023), 2023.11, [URL]. |
| 10. | Yusuke Miyake,Tsunenori Mine, Contextual and Nonstationary Multi-armed Bandits Using the Linear Gaussian State Space Model for the Meta-Recommender System, 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 3138-3145, 2023.10. |
| 11. | Bo Wang and Tsunenori Mine, Optimizing Upstream Representations for Out-of-Domain Detection with Supervised Contrastive Learning, 32nd ACM International Conference on Information and Knowledge Management (CIKM2023), 2023.10. |
| 12. | Landy Rajaonarivo, Tsunenor Mine, Yutaka Arakawa, Few-shot and LightGCN learning for multi-label estimation of lesser-known tourist sites using tweets, the 22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, 2023.10, [URL]. |
| 13. | Menna Fateen, Tsunenori Mine:, Using Similarity Learning with SBERT to Optimize Teacher Report Embeddings for Student Performance Prediction, The 24th International Conference on Artificial Intelligence in Education, 720-726, Communications in Computer and Information Science 1831, Springer, 2023.07. |
| 14. | Sei-ichiro Kamata, Tsunenori Mine, Comments on Quasi-Linear Support Vector Machine for Nonlinear Classification, IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, https://doi.org/10.1587/transfun.2022EAL2051, E106-A, 11, 論文ID 2022EAL2051, 2023.05. |
| 15. | Ristu Saptono, Tsunenori Mine, Distribution-adapted Model For Helpful Vote Prediction, IEEE Access, 10.1109/ACCESS.2022.3220781, 10, 125194-125211, 2022.12, [URL]. |
| 16. | Ristu Saptono,Tsunenori Mine, Adaptive Neighborhood Distribution-based Model for Estimating Helpful Votes of Customer Review, The 21st IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology: WI-IAT 2022, 143-150, 2022.11, [URL]. |
| 17. | Yuichi Ishikawa, Roberto Legaspi, Kei Yonekawa, Yugo Nakamura, Shigemi Ishida, Tsunenori Mine, and Yutaka Arakawa, Unsupervised Learning of Domain-Independent User Attributes, IEEE Access, 10.1109/ACCESS.2022.3220781, 10, 119649-119665, 2022.11. |
| 18. | Shaowen Peng, Kazunari Sugiyama and Tsunenori Mine, SVD-GCN: A Simplified Graph Convolution Paradigm for Recommendation, 31st ACM International Conference on Information and Knowledge Management (CIKM2022), https://doi.org/10.1145/3511808.3557462, 1625-1634, 2022.10. |
| 19. | Ristu Saptono,Tsunenori Mine, Best Approximate Distribution-based Model for Helpful Vote of Customer Review Prediction, 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 3427-3434, accepted as a regular paper, 2022.10. |
| 20. | Shaowen Peng, Kazunari Sugiyama and Tsunenori Mine, Less is More: Reweighting Important Spectral Graph Features for Recommendation, ACM SIGIR 2022, 1273-1282, 2022.07, [URL]. |
| 21. | Menna Fateen, Tsunenori Mine:, Extraction of Useful Observational Features from Teacher Reports for Student Performance Prediction, The 23rd International Conference on Artificial Intelligence in Education, 620-625, 2022.07, [URL]. |
| 22. | Landy Rajaonarivo, Tsunenor Mine, Yutaka Arakawa, Coupling of semantic and syntactic graphs generated via tweets to detect local events, 14th International Conference on E-Service and Knowledge Management (ESKM 2022), 128-133, 2022.07. |
| 23. | Makoto Yamada, Tsunenor Mine, Modality estimation methods in internal training reflection texts using BERT, 14th International Conference on E-Service and Knowledge Management (ESKM 2022), 118-123, 2022.07. |
| 24. | Shumpei Kobashi, Tsunenor Mine, A System for Generating Student Progress Reports in Cram School, 14th International Conference on E-Service and Knowledge Management (ESKM 2022), 43-48, 2022.07. |
| 25. | Kyouhei Ueno, Tsunenor Mine, Automatic assessment of student understanding for estimating test score, 12th International Conference on Learning Technologies and Learning Environments (LTLE2022), 224-229, 2022.07. |
| 26. | Bo Wang and Tsunenori Mine, Practical and Efficient Out-of-Domain Detection with Adversarial Learning, The 37th ACM/SIGAPP Symposium On Applied Computing, 844-853, 2022.04, [URL]. |
| 27. | Landy Rajaonarivo, Tsunenor Mine, Yutaka Arakawa, Automatic Generation of Event Ontology from Social Network and Mobile Positioning Data, the 20th IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 87-94, 2021.12, [URL]. |
| 28. | Kohei Yamaguchi, Tsunenori Mine, Estimation of Precedence Relations to Deal with Regional Complaint Reports, the 5th IEEE International Conference on Agents (IEEE-ICA 2021), 7-12, 2021.12, [URL]. |
| 29. | Menna Fateen, Kyouhei Ueno, Tsunenori Mine, An Improved Model to Predict Student Performance Using Teacher Observation Reports, 29TH INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION 2021, 1, 31-40, 2021.11. |
| 30. | Shumpei Kobashi, Tsunenori Mine, Generating Student Progress Reports Based on Keywords, 29TH INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION 2021, 1, 75-80, 2021.11. |
| 31. | Takuya Kawatani, Tsuneonri Mine, Determination of Collection Points of Bus Probe Data to Achieve High Prediction Performance and Low Collection Cost, ICMU2021, 1-6, 2021.11. |
| 32. | Menna Fateen, Tsunenori Mine, Predicting Student Performance Using Teacher Observation Reports, EDM 2021, 2021.07. |
| 33. | Takuya Kawatani, Tsubasa Yamaguchi, Yuta Sato, Ryotaro Maita, Tsuneonri Mine, Prediction of bus travel time over intervals between pairs of adjacent bus stops using city bus probe data, International Journal of Intelligent Transportation Systems Research, https://doi.org/10.1007/s13177-021-00251-8, 19, 456-467, 2021.04. |
| 34. | Jihed Makhlouf, Tsunenori Mine, Mining Students’ Comments to Build an Automated Feedback System, The 13th International Conference on Computer Supported Education (CSEDU2021), 1, 15-24, 2021.04. |
| 35. | Yuta Sato, Takuya Kawatani, Tsunenori Mine, Influence of Weather Features to Determine Sudden Braking, International Journal of Intelligent Transportation Systems Research, https://doi.org/10.1007/s13177-021-00253-6, 19, 366-377, 2021.02. |
| 36. | Hanwei Zhang, Hiroshi Kawasaki, Tsunenori Mine, Shintaro Ono, Focusing on Discrimination between Road Conditions and Weather in Driving Video Analysis, The 27th International Workshop on Frontiers of Computer Vision, 12pages, 2021.02. |
| 37. | Haibo Yu, Qiang Sun, Kejun Xiao, Yuting Chen, Tsunenori Mine, Jianjun Zhao, Parallelizing Flow-Sensitive Demand-Driven Points-to Analysis, 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C), 10.1109/QRS-C5114.2020.00026, 91-97, 2020.12, [URL]. |
| 38. | Ristu Saptono and Tsunenori Mine, Time-based Sampling Methods for Detecting Helpful Reviews, The 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT2'0), 2020.12, [URL]. |
| 39. | Jihed Makhlouf, Tsunenori Mine, Automatic Feedback Models to Students Freely Written Comments, 28TH INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION, 2020.11, [URL]. |
| 40. | Tsuneno Nakanishi, Yutaka Arakawa, Takahiro Ando, Shigemi Ishida, Kenji Hisazumi, Tsunenori Mine, Akira Fukuda, An Inter-Organizational Software Architecture for Smart Mobility, The 9th International Conference on Software and Information Engineering, 2020.11. |
| 41. | Jihed Makhlouf, Tsunenori Mine, Analysis of Click-Stream Data to Predict STEM Careers from Student Usage of an Intelligent Tutoring System, Journal of Educational Data Mining, 10.5281/zenodo.4008050, 12, 2, 1-18, 2020.08, [URL]. |
| 42. | Jihed Makhlouf, Tsunenori Mine, Prediction Models for Automatic Assessment to Student Free-written Comments, CSEDU2020, 10.5220/0009580300770086, 77-86, 2020.05, [URL]. |
| 43. | Shaowen Peng and Tsunenori Mine, Mixture-Preference Bayesian Matrix Factorization for implicit feedback datasets, The 35th ACM/SIGAPP Symposium On Applied Computing, 1427-1434, 2020.04. |
| 44. | Jihed Makhlouf, Tsunenori Mine, Predicting Student Exam Scores Based on Click-stream Level Data of Their Usage of an E-book System, LAK20 Data Challenge, 2020.03, [URL]. |
| 45. | Ismail Parewai, Mansur As, Tsunenori Mine, Mario Koeppen, Identification and Classification of Sashimi Food Using Multispectral Technology, 2nd Asia Pacific Information Technology Conference, APIT 2020 APIT 2020 - 2020 2nd Asia Pacific Information Technology Conference, 10.1145/3379310.3379317, 66-72, 2020.01, Food quality inspection is an essential factor in our daily lives. Food inspection is analyzing heterogeneous food data from different sources for perception, recognition, judgment, and monitoring. This study aims to provide an accurate system in image processing techniques for the inspection and classification of sashimi food damage based on detecting external data. The external texture was identified based on the visible and invisible system that was acquired using multispectral technology. We proposed the Grey Level Co-occurrence Matrix (GLCM) model for analysis of the texture features of images and the classification process was performed using Artificial Neural Network (ANN) method. This study showed that multispectral technology is a useful system for the assessment of sashimi food and the experimental also indicates that the invisible channels have the potential in the classification model, since the hidden texture features that are not clearly visible to the human eye.. |
| 46. | Mansur As, Tsunenori Mine, Tsubasa Yamaguchi, Prediction of Bus Travel Time Over Unstable Intervals between Two Adjacent Bus Stops, International Journal of Intelligent Transportation Systems Research, 10.1007/s13177-018-0169-3, 18, 1, 53-64, 2020.01, This paper addresses the problem of predicting bus travel time over unstable intervals between two adjacent bus stops using two types of machine learning techniques: ANN and SVR methods. Our model considers the variability of travel time because the travel time is often influenced by stochastic factors, which increase the variance of travel time over an interval between inter-time periods. The factors also affect the variance of the travel time over the interval at the same time period between inter-days. In addition, the factors show some correlation of travel time over the interval between time periods in a day. The performance of the proposed model is validated with real bus probe data collected from November 21st to December 20th, 2013, provided by Nishitetsu Bus Company, Fukuoka, Japan. We demonstrated the impact of two types of input variables for the prediction in off- and on-peak (rush hour) periods. The results show that the two types of inputs can effectively improve the prediction accuracy. Moreover, we compared the proposed method with our previous methods. The experimental results show the validity of our proposed method.. |
| 47. | Naoto Kai, Kota Sakasegawa, Tsunenori Mine and Sachio Hirokawa, Machine Learning of Ambiguous Sentences in Technical Manual for Tacit Knowledge Acquisition, IEEE/IIAI International Congress on Applied Information Technology (IEEE/IIAI AIT 2019), 10.1109/AIT49014.2019.9144929, 1-5, 2019.11, [URL]. |
| 48. | Takuya Kawatani, Eisuke Itoh, Sachio Hirokawa, Tsunenori Mine, Location does not always determine sudden braking, 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019, 10.1109/ITSC.2019.8917480, 875-882, 2019.10, Understanding conditions and situations causing sudden braking is important for preventing traffic accidents. Previous studies have used probe vehicle data to detect risky positions where sudden braking frequently occurred. However, they have mainly focused on vehicle-related factors.In this paper, we propose a novel method for discriminating sudden braking. Unlike previous studies, the method exhaustively explores probe data including temporal factors, constructs a large number of features combining pairs of feature names and their values, and applies the Support Vector Machine classifier and Feature Selection method to the features. To conduct the experiments, we used probe data provided by the Aizu-Wakamatsu City Open Data Utilization Verification Project. The proposed method discriminated sudden braking quite accurately, with a discrimination performance averaging an F1 measure of 93.2%. We also found that the probability of the occurrence of sudden braking is not always high at locations where sudden braking frequently occurred, but rather, temporal factors such as date and time, or day of week are strongly related to performance in discriminating sudden braking with high probability.. |
| 49. | Ryo Fujii, Takahiro Ando, Kenji Hisazumi, Tsunenori Mine, Tsuneo Nakanishi, and Akira Fukuda, Architecture and Development of Agent-based Unified Simulation Environment for ITS Services, Intelligent Transport Systems for Everyone's Mobility, 10.1007/978-981-13-7434-0, 227-246, 2019.07. |
| 50. | 峯 恒憲, Prediction of Travel Time over Unstable Intervals between Adjacent Bus Stops Using Historical Travel Time in both previous and current time periods, Intelligent Transport Systems for Everyone's Mobility, 227-246, 2019.07. |
| 51. | Yusuke Tozaki, Takahiko Suzuki, Tsunenori Mine, Sachio Hirokawa, Extracting Irregular Datasets in University Admission Statistics using Text Mining and Benford's Law, 8th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2019 Proceedings - 2019 8th International Congress on Advanced Applied Informatics, IIAI-AAI 2019, 10.1109/IIAI-AAI.2019.00207, 1023-1024, 2019.07, It is known as Benford's law that the distribution of the first digits forms a specific shape for natural numerical datasets. Deviation from the Benford's distribution indicates the irregularity of the dataset. However, it does not tell any clue to interpret the reason of irregularity. The present paper constructs a search engine of cells that appear in tables by correlating a cell with the words in the title of row or column or in the explanation of the table. We generate an exhaustive dataset of cells for testing irregularity by enumerating the search conditions. We applied the method to the number of applicants, the number of candidates, and the number of successful applicants in each department of 565 private universities in Japan. We confirmed the effectiveness of the proposed method by extracting the characteristics of the irregular datasets.. |
| 52. | Takuya Kawatani, Eisuke Itoh, Sachio Hirokawa, Tsunenori Mine, Machine Learning and Visualization of Sudden Braking using Probe Data, 8th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2019 Proceedings - 2019 8th International Congress on Advanced Applied Informatics, IIAI-AAI 2019, 10.1109/IIAI-AAI.2019.00024, 67-72, 2019.07, This paper presents a novel mining and visualizing tool that detects features to estimate sudden braking. The tool uses a machine learning and feature selection method to find the features exhaustively from combinations of the features which include not only vehicle-related factors, but also outer circumstances or temporal factors. The tool also obtains the locations inferred by the features detected. A normal way would first search for locations where sudden braking behavior frequently occurred, but it is not always true that the occurrence probability of sudden braking at the locations is high. On the other hand, our tool finds the locations related to sudden braking with high probability, more than 98%. Through the visualizing process, the features can be used as clues to find new factors which affect sudden braking.. |
| 53. | Jihed Makhlouf, Tsunenori Mine, Investigating Reading Behaviors within Student Reading Sessions to Predict their Performance, LAK19 Data Challenge International Workshop on Predicting Performance Based on the Analysis of Reading Behavior: A Data Challenge 2019, 2019.03, [URL]. |
| 54. | Tsunenori Mine, Sachio Hirokawa, Takahiko Suzuki, Does crime activity report reveal regional characteristics?, 13th International Conference on Ubiquitous Information Management and Communication, IMCOM 2019 Proceedings of the 13th International Conference on Ubiquitous Information Management and Communication, IMCOM 2019, 10.1007/978-3-030-19063-7_46, 582-598, 2019.01, Crime is one of the most important social problems for administrative region. Ascertaining the detailed characteristics of crime and preparing countermeasures are important to keep community life safe and secure. A lot of studies using crime data and geographical data have been carried out with a view to crime prevention. These studies include analyzing geographical features of crime, mapping crime-related information and crime hotspots on the map, predicting crime rate and so on. In addition, police stations have recently begun emailing notifications regarding crime to citizens to help them avoid crime. The e-mail messages include rich information about regional crime; they are actively used by services providing guidance to people in how to avoid crime. These services map the messages onto regional maps using the location information in the messages and show the relations between the locations and crime on the map. In addition, some services send alarms to their users when the GPS information of the users indicates that they are passing by the places where crime has occurred. However, these services only use the location and crime information extracted from the messages. Thus, we cannot say the messages have been fully used to clarify characteristics of regional crime. Therefore, in this paper, we investigate whether or not the crime messages sent by e-mail can be further exploited as a valid source for analyzing the criminal characteristics of a region, i.e., whether or not they include the characteristics of regional crime. To this end, in this research, we conducted experiments to make clear whether or not the crime messages sent by e-mail can help to distinguish regions. Experimental results illustrate that the contents of e-mail crime messages helped to distinguish regions having greater than or equal to 100 reports, with an average F-measure of about 90.3%, while only using the names of the areas where crime has occurred cannot match that F-measure.. |
| 55. | Tsubasa Yamaguchi, Mansur As, Tsunenori Mine, Prediction of Bus Delay over Intervals on Various Kinds of Routes Using Bus Probe Data, 5th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2018 Proceedings - 5th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2018, 10.1109/BDCAT.2018.00020, 97-106, 2018.12, Prediction of bus travel time and/or delay time is a useful tool for passengers who want to plan their journey, e.g., when they should leave from the origin bus stop, what they will do after arriving at the destination bus stop, and so on. Many studies have tackled this task using probe data and/or the real time data provided by automatic vehicle location (AVL) systems. Most of them only targeted a small number of routes, short time periods, e.g. less than one week, and used few machine learning models to evaluate their methods. However, different routes generally show different characteristics. In fact, there are big differences between urban routes and rural routes. Furthermore, the performance of machine learning models also varies according to the data dealt with by the models. In this paper, we propose prediction models for bus delay over all intervals between pairs of adjacent bus stops. To build the models, we use one month of bus probe data, which includes more than 80 routes, and apply several machine learning models: linear regression (LR), artificial neural network (ANN), support vector regression (SVR), random forest (RF), and gradient boosting decision tree (GBDT). Experimental results demonstrate the superiority of the GBDT-based prediction model and the effects of considering travel time over prior intervals.. |
| 56. | Haibo Yu, Xi Jia, Tsunenori Mine, Jianjun Zhao, Type conversion sequence recommendation based on semantic web technology, 4th IEEE SmartWorld, 15th IEEE International Conference on Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018 Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018, 10.1109/SmartWorld.2018.00076, 240-245, 2018.12, As the software systems are becoming more and more complicated, developers have an increasing dependency on code recommendation tools to assist them to fulfill their development tasks. However, the current historical-code-based recommendation methods are directly affected by the quality of the historical codes and the program-environment-information-based recommendation methods cannot provide satisfactory recommendation results for static methods because it is difficult to know all possible static members only using the program context, and even if we know all the static members, we still cannot add all of them to the entry point for search because its large number may cause a space explosion. In this paper, we propose a type conversion sequence recommendation method based on program environment information. Combing with the reachability analysis using semantic Web technology, the proposed method tries to reduce the searching entry points to solve the space explosion problem caused by the recommendation of static methods. We implemented an Eclipse plug-in based on the proposed method and conducted experiments on Tomcat source code. The experimental results showed that the proposed method can not only recommend type conversion sequences with static methods effectively, but also has a higher accuracy for the recommendation of object methods compared with the Eclipse Code Recommenders.. |
| 57. | Mansur As, Tsunenori Mine, Tsubasa Yamaguchi, Prediction of Bus Travel Time over Unstable Intervals between Two Adjacent Bus Stops, International Journal of Intelligent Transportation Systems Research, 1-12, 2018.11. |
| 58. | Mansur As, Tsunenori Mine, Hiroyuki Nakamura, Estimation of Travel Time Variability Using Bus Probe Data, 6th IEEE International Conference on Advanced Logistics and Transport, ICALT 2017 6th IEEE International Conference on Advanced Logistics and Transport, ICALT 2017 - Proceedings, 10.1109/ICAdLT.2017.8547006, 199-204, 2018.11, Prediction of bus travel times is of crucial importance for passengers in letting them know their departure time from an origin and arrival time at a destination and allowing them to make decisions (e.g., postpone departure time at certain hours) and to reduce their waiting time at bus stops. To predict bus travel times, it is important to know whether the target routes are stable or not. In this paper, we propose a time series approach to predict the travel time over an interval between two adjacent bus stops. We build Artificial Neural Network (ANN) models to predict the travel time over the interval. To make accurate predictions, we divide a day into 8 time-periods in calculating travel time over the interval and classify unstable intervals into three types: weak, medium and strong unstable. We use bus probe data collected from November 21st to December 20th 2013 and provided by Nishitetsu Bus Company, Fukuoka, Japan. Experimental results show that our models can effectively improve the prediction accuracy of travel times over intervals by focusing on the three unstable classes and calculating travel times for each interval at each of 8 time-periods in a day.. |
| 59. | Shaowen Peng, Xianzhong Xie, Tsunenori Mine, Chang Su, Vector representation based model considering randomness of user mobility for predicting potential users, Principles and Practice of Multi-Agent Systems - 21st International Conference, 2018, Proceedings, 10.1007/978-3-030-03098-8_5, 70-85, 2018.10, With increasing popularity of location-based social networks, POI recommendation has received much attention recently. Unlike most of the current studies which provide recommendations from perspective of users, in this paper, we focus on the perspective of Point-of-Interest (POI) for predicting potential users for a given POI. We propose a novel vector representation model for the prediction. Many current matrix factorization-based methods only pay attention to combining new information and basic matrix factorization, while in our model, we improve the matrix factorization model itself by replacing dot product with cosine similarity. We also address the problem of randomness of user’s check-in behavior by applying deep neural network to modeling the relationships between the user’s current check-in and context information of current check-in. Extensive experiments conducted on two real-world datasets demonstrate the superior performance of our proposed model and the effectiveness of the factors incorporated in our model.. |
| 60. | Tsunenori Mine, Shiro Mise, Hiroyuki Nakamura, Takuya Hiraoki, Shiori Koga, Takahiro Ando, Hisazumi Kenji, Tsuneo Nakanishi, Akira Fukuda, ItoCamLife A Platform of Sharing and Recommending Information Considering User Contexts to Facilitate Smart Mobility, 7th International Congress on Advanced Applied Informatics, IIAI-AAI 2018 Proceedings - 2018 7th International Congress on Advanced Applied Informatics, IIAI-AAI 2018, 10.1109/IIAI-AAI.2018.00030, 109-114, 2018.07, People do not always know about everything in the whole area even where they go about their daily life. Visitors to the area still more do not know about the area such as facilities and/or when and where to hold events in the area, means of transport to/from the area, and means of movements in the area if the area is too large for visitors to walk around, and so on. Although the main Web site of a local area such as a region, district, park or an organization usually works as a portal and provides the information above, the information is not always linked to with each other, in particular, on the map of the area except for facility names. Therefore people often feel difficult to find information related to their current or specified positions. Considering these problems, in this paper, we discuss an information sharing and recommendation platform specialized to a local area. The platform provides a variety of information associated with a map of the area, which means the information is linked with each other through the map. As a case study, we present 'ItoCamLife,' which targets Ito Campus of Kyushu University. Ito Campus is one of four campuses in Kyushu University and the largest campus in Japan as one campus. More than 10 thousand people including students, members of faculty and staffs are commuting, and many visitors are also coming there especially when a big event such as university festival or a large scale conference is held. Therefore, Ito Campus needs such a platform of sharing and recommending information. In this paper, we present an overview of ItoCamLife, including its concept and current functions.. |
| 61. | Takahiro Ando, Ryo Fujii, Hisazumi Kenji, Tsunenori Mine, Tsuneo Nakanishi, Akira Fukuda, Overview and Application Examples of Agent-Based Unified Simulation Environment, 7th International Congress on Advanced Applied Informatics, IIAI-AAI 2018 Proceedings - 2018 7th International Congress on Advanced Applied Informatics, IIAI-AAI 2018, 10.1109/IIAI-AAI.2018.00027, 92-97, 2018.07, Agent-based traffic simulation has become more and more attractive and important to develop new ITS (Intelligent Transport Systems) services. So far a variety of studies and developments that combine simulators and evaluate ITS services on the combined simulators have been conducted. In this paper, we introduce a simulation environment, called Agent-based USE (Agent-based Unified Simulation Environment), and some application examples for ITS services. The Agent-based USE provides an easy-to-build simulation environment for ITS-related services. In particular, by connecting simulators with ITS services, the Agent-based USE determines behaviors to be changed on the simulators using the data of the services such as recommendation results generated by the services, tells the decisions to simulators; the Agent-based USE then obtains the data representing the current situation on the simulators and sends the data to the services as feedback so as to enable the services to generate the next recommendation. In addition, by using the Agent-based USE, it is possible to construct a co-simulation environment where simulation is performed by synchronizing some kinds of simulators and services and by sharing each simulation information. In this paper, we introduce the overview and architecture of the Agent-based USE for traffic simulation, and discuss its usefulness through some application examples.. |
| 62. | Tsuneo Nakanishi, Hisazumi Kenji, Takahiro Ando, Tsunenori Mine, Akira Fukuda, Software Engineering Practices for the Smart Mobility Market, 7th International Congress on Advanced Applied Informatics, IIAI-AAI 2018 Proceedings - 2018 7th International Congress on Advanced Applied Informatics, IIAI-AAI 2018, 10.1109/IIAI-AAI.2018.00031, 115-120, 2018.07, Smart mobility services evolve rapidly in excessive competition with rivals in the market. Meanwhile, service suppliers cooperate partially to avoid exhaustion and concentrate on their core business. Therefore, homebrew and external services have dependency one another. This paper proposes some software engineering practices to develop and operate such smart mobility services. An interorganizational architecture is imported from the ITS domain as a shared view for service suppliers in competition and cooperation. Each service supplier construct an intraorganizational architecture for its home-brew services in microservice architecture style. Technical practices are basically feature oriented. Services are comprehended by the feature model and their boundaries are managed based on it. Supply chain management of services is conducted based on the data flow diagram traceable from the feature model. The contract and its variation on service supply is managed and accounted by the assurance case. Risks on sustainable service supply are studied with failure modes and effects analysis.. |
| 63. | Akira Fukuda, Tsuneo Nakanishi, Kenji Hisazumi, Kunihiko Kaneko, Shigeaki Tagashira, Tsunenori Mine, Yutaka Arakawa, Shigemi Ishida, Takahiro Ando, Shuichi Ashihara, Masakatsu Ura, Yoshimichi Nakamura, Soichiro Nakamura, Weiqiang Kong, Guoqiang Li, Toward Sustainable Smart Mobility Information Infrastructure Platform - Current Status - Current S, 7th International Congress on Advanced Applied Informatics, IIAI-AAI 2018 Proceedings - 2018 7th International Congress on Advanced Applied Informatics, IIAI-AAI 2018, 10.1109/IIAI-AAI.2018.00025, 81-85, 2018.07, Smart mobility systems, which include Intelligent Transportation Systems(ITS) and smart energy systems, become more important. There is, however, lack of its platform studies. We started a sustainable information infrastructure project for smart mobility systems. The project pursues issues that establish an information infrastructure architecture and seamless development method chain for it. The project has mainly two features; 1) applying life-cycle-oriented methods, which are a cycle from system development to operations, to a real world, and 2) dealing with an uncertainty in system design phase. This paper describes current status of the project.. |
| 64. | Jihed Makhlouf, Tsunenori Mine, Investigating How School-Aggregated Data Can Influence in Predicting STEM Career from Student usage of an Intelligent Tutoring System, EDM 2018 Workshop on Scientific Findings from the ASSISTments Longitudinal Data (2018), 2018.07, [URL]. |
| 65. | Jihed Makhlouf, Tsunenori Mine, Predicting if students will pursue a STEM career using School-Aggregated Data from their usage of an Intelligent Tutoring System, EDM(Educational Data Mining) 2018, 552-555, 2018.07, [URL]. |
| 66. | Mansur As, Tsunenori Mine, Dynamic bus travel time prediction using an ANN-based model, 12th International Conference on Ubiquitous Information Management and Communication, IMCOM 2018 Proceedings of the 12th International Conference on Ubiquitous Information Management and Communication, IMCOM 2018, 10.1145/3164541.3164630, 2018.01, Prediction of bus travel time is one of crucial issues for passengers in letting them know their departure time from an origin and arrival time at a destination and allowing them to make decisions (e.g., postpone departure time at certain hours) and to reduce their waiting time at bus stops. This paper proposes a time series approach to predict travel time over an interval between two adjacent bus stops. We build an Artificial Neural Network (ANN) model to predict travel time over the interval. To make accurate prediction, we divide a day into 8 time-periods in calculating travel time over the interval at each time-period and also use the travel time condition at right before the target time-period in order to apply the dynamical change of travel time as well as the historical average travel time at the same time-period during the past several days. To validate the proposed method, we used bus probe data collected from November 21st to December 20th in 2013, provided by Nishitetsu Bus Company, Fukuoka, Japan. Experimental results show that our models can effectively improve prediction accuracy of travel time on the route compared to a method only using the historical average travel time.. |
| 67. | Yao Lin, Kohei Yamaguchi, Tsunenori Mine, Sachio Hirokawa, Is SVM+FS better to satisfy decision by majority?, 3rd International Conference on Soft Computing and Data Mining, SCDM 2018 Recent Advances on Soft Computing and Data Mining - Proceedings of the 3rd International Conference on Soft Computing and Data Mining SCDM 2018, 10.1007/978-3-319-72550-5_26, 261-271, 2018.01, Government 2.0 activities have become very attractive and popular. Using the platforms to support the activities, anyone can anytime report issues in a city on the Web and share the reports with other people. Since a variety of reports are posted, officials in the city management section have to give priorities to the reports. However, it is not easy task to judge the importance of the reports since importance judgments vary depending on the officials and consequently the agreement rate becomes low. To remedy the low agreement rate problem of human judgment, it is necessary to create an automatic method to find reports with high priorities. Hirokawa et al. employed the Support Vector Machine (SVM) with word feature selection method (SVM+FS) to detect signs of danger from posted reports because signs of danger is one of high priority issues to be dealt with. However they did not compare the SVM+FS method with other conventional machine learning methods and it is not clear whether or not the SVM+FS method has better performance than the other methods. This paper compared the results of the SVM+FS method with conventional machine learning methods: SVM, Random Forest, and Naïve Bayse with conventional word vectors, an LDA-based document vector, and word embedding by Word2Vec. Experimental results illustrate the validity and effectiveness of the SVM+FS method.. |
| 68. | Akira Fukuda, Kenji Hisazumi, Tsunenori Mine, Shigemi Ishida, Takahiro Ando, Shota Ishibashi, Shigeaki Tagashira, Kunihiko Kaneko, Yutaka Arakawa, Weiqiang Kong, Guoqiang Li, Toward sustainable smart mobility information infrastructure platform Project overview, Studies in Computational Intelligence, 10.1007/978-3-319-70636-8_3, 35-46, 2018.01, Smart mobility systems, which include Intelligent Transportation Systems (ITS) and smart energy ones, become more important. There is, however, lack of its platform studies. This paper proposes a sustainable information infrastructure project for smart mobility systems. The project pursues issues that establish an information infrastructure architecture and a seamless development method chain for it. The project has mainly two features: (1) applying life-cycle-oriented methods, which are a cycle from system development phase to operation phase. In addition, these methods are applied to real world applications, and (2) dealing with an uncertainty that occurs in system development upper phase. This paper describes an overview of the project.. |
| 69. | Mansur As, Tsunenori Mine, Dynamic bus travel time prediction using an ANN-based model, ACM International Conference Proceeding Series, 10.1145/3164541.3164630, 20:1-20:8, 2018.01, Prediction of bus travel time is one of crucial issues for passengers in letting them know their departure time from an origin and arrival time at a destination and allowing them to make decisions (e.g., postpone departure time at certain hours) and to reduce their waiting time at bus stops. This paper proposes a time series approach to predict travel time over an interval between two adjacent bus stops. We build an Artificial Neural Network (ANN) model to predict travel time over the interval. To make accurate prediction, we divide a day into 8 time-periods in calculating travel time over the interval at each time-period and also use the travel time condition at right before the target time-period in order to apply the dynamical change of travel time as well as the historical average travel time at the same time-period during the past several days. To validate the proposed method, we used bus probe data collected from November 21st to December 20th in 2013, provided by Nishitetsu Bus Company, Fukuoka, Japan. Experimental results show that our models can effectively improve prediction accuracy of travel time on the route compared to a method only using the historical average travel time.. |
| 70. | Tsunenori Ishioka, Kohei Yamaguchi, Tsunenori Mine, Rubric-based Automated Japanese Short-answer Scoring and Support System Applied to QALab-3, Proceedings of the 13th NTCIR Conference on Evaluation of Information Access Technologies, 152-158, 2017.12, [URL]. |
| 71. | Masaki Maruta, Tsunenori Mine, Detecting Communication Situations Using Smartphone Sensors - Toward Real SNS - Toward, 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017 Proceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017, 10.1109/IIAI-AAI.2017.157, 465-470, 2017.11, Connections between people are important in social life. The connections are usually recorded using business cards in business situations. However, opportunities for encounters to create a connection are rarely recorded, if people do not take the trouble of recording them. This is especially true concerning information regarding the place or situation that afforded the connection opportunity. That makes it difficult to reuse the connection information. Much research has been conducted so far on automatically detecting situations of a connection between two people. However, this research usually relies on special sensors or tools to recognize the connection. Such sensors or tools are unfortunately not usually readily available in daily life, and people do not want to carry additional sensors on a daily basis if they are only specialized to serve the purpose of recognizing connections. This paper proposes a method to detect situations in the connections between people using the BLE functions, acceleration sensors, microphone and recorder built into an ordinary smartphone. The objective in this research is to make clear the possibilities and the limitations of the proposed method in detecting peoples connection situations. Experimental results suggest that the proposed method can detect the conversation situation between people with their smartphones in their pocket or bag who are standing within a short distance of each other of less than one meter.. |
| 72. | Masaki Maruta, Tsunenori Mine, Detecting Communication Situations Using Smartphone Sensors - Toward Real SNS - Toward, Proceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017, 10.1109/IIAI-AAI.2017.157, 465-470, 2017.11, Connections between people are important in social life. The connections are usually recorded using business cards in business situations. However, opportunities for encounters to create a connection are rarely recorded, if people do not take the trouble of recording them. This is especially true concerning information regarding the place or situation that afforded the connection opportunity. That makes it difficult to reuse the connection information. Much research has been conducted so far on automatically detecting situations of a connection between two people. However, this research usually relies on special sensors or tools to recognize the connection. Such sensors or tools are unfortunately not usually readily available in daily life, and people do not want to carry additional sensors on a daily basis if they are only specialized to serve the purpose of recognizing connections. This paper proposes a method to detect situations in the connections between people using the BLE functions, acceleration sensors, microphone and recorder built into an ordinary smartphone. The objective in this research is to make clear the possibilities and the limitations of the proposed method in detecting peoples connection situations. Experimental results suggest that the proposed method can detect the conversation situation between people with their smartphones in their pocket or bag who are standing within a short distance of each other of less than one meter.. |
| 73. | Tsunenori Mine, Shaymaa E. Sorour, Kazumasa Goda, Artificial Intelligence and Education -- Comment mining project toward improving student learning performance - an Example --, the 1st international scientific conference of the Faculty of Specific Education, Kafrelsheikh University, 2017.10, [URL]. |
| 74. | Sachio Hirokawa, Takahiko Suzuki, Tsunenori Mine, Machine learning is better than human to satisfy decision by majority, 16th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017 Proceedings - 2017 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017, 10.1145/3106426.3106520, 694-701, 2017.08, Government 2.0 activities have become very attractive and popular these days. Using platforms to support the activities, anyone can anytime report issues or complaints in a city with their photographs and geographical information on the Web, and share them with other people. Since a variety of reports are posted, officials in the city management section have to check the importance of each report and sort out their priorities to the reports. However, it is not easy task to judge the importance of the reports. When several officials work on the task, the agreement rate of their judgments is not always high. Even if the task is done by only one official, his/her judgment sometimes varies on a similar report. To remedy this low agreement rate problem of human judgments, we propose a method of detecting signs of danger or unsafe problems described in citizens' reports. The proposed method uses a machine learning technique with word feature selection. Experimental results clearly explain the low agreement rate of human judgments, and illustrate that the proposed machine learning method has much higher performance than human judgments.. |
| 75. | Sachio Hirokawa, Takahiko Suzuki, Tsunenori Mine, Machine learning is better than human to satisfy decision by majority, Proceedings - 2017 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017, 10.1145/3106426.3106520, 694-701, 2017.08, Government 2.0 activities have become very attractive and popular these days. Using platforms to support the activities, anyone can anytime report issues or complaints in a city with their photographs and geographical information on the Web, and share them with other people. Since a variety of reports are posted, officials in the city management section have to check the importance of each report and sort out their priorities to the reports. However, it is not easy task to judge the importance of the reports. When several officials work on the task, the agreement rate of their judgments is not always high. Even if the task is done by only one official, his/her judgment sometimes varies on a similar report. To remedy this low agreement rate problem of human judgments, we propose a method of detecting signs of danger or unsafe problems described in citizens' reports. The proposed method uses a machine learning technique with word feature selection. Experimental results clearly explain the low agreement rate of human judgments, and illustrate that the proposed machine learning method has much higher performance than human judgments.. |
| 76. | Ryo Fujii, Takahiro Ando, Kenji Hisazimi, Tsunenori Mine, Tsuneo Nakanishi, and Akira Fukuda, Development of Support Environment Towards Traffic Simulation for ITS Services, Proc. the 15th Int. Conf. on Software Engineering Research and Practice (SERP’17), 98-103, 2017.07. |
| 77. | Shaymaa E. Sorour, Kazumasa Goda, Tsunenori Mine, Comment Data Mining to Estimate Student Performance Considering Consecutive Lessons, EDUCATIONAL TECHNOLOGY & SOCIETY, 20, 1, 73-86, 2017.01, [URL], The purpose of this study is to examine different formats of comment data to predict student performance. Having students write comment data after every lesson can reflect students' learning attitudes, tendencies and learning activities involved with the lesson. In this research, Latent Dirichlet Allocation (LDA) and Probabilistic Latent Semantic Analysis (pLSA) are employed to predict student grades in each lesson. In order to obtain further improvement of prediction results, a majority vote method is applied to the predicted results obtained in consecutive lessons. The research findings show that our proposed method continuously tracked student learning situations and improved prediction performance of final student grades.. |
| 78. | Shaymaa E. Sorour, Kazumasa Goda, Tsunenori Mine, Comment data mining to estimate student performance considering consecutive lessons, Educational Technology and Society, 20, 1, 73-86, 2017.01, The purpose of this study is to examine different formats of comment data to predict student performance. Having students write comment data after every lesson can reflect students' learning attitudes, tendencies and learning activities involved with the lesson. In this research, Latent Dirichlet Allocation (LDA) and Probabilistic Latent Semantic Analysis (pLSA) are employed to predict student grades in each lesson. In order to obtain further improvement of prediction results, a majority vote method is applied to the predicted results obtained in consecutive lessons. The research findings show that our proposed method continuously tracked student learning situations and improved prediction performance of final student grades.. |
| 79. | Yuta Sano, Tsunenori Mine, Detection of current actual status and demand expressions in community complaint reports, Transactions of the Japanese Society for Artificial Intelligence, 10.1527/tjsai.AG16-B, 32, 5, AG16-B_1-AG16-B_10, 2017.01, Government 2.0 activities have become attractive and popular these days. Using tools of their activities, anyone can report issues or complaints in a city on the Web with their photographs and geographical information, and share their information with other people. On the other hand, unlike telephone calls, the concreteness of a report depends on its reporter. Thus, the actual status and demand to the status may not be described clearly or either one may be miss-described in the report. It may accordingly happen that officials in the city management section can not grasp the actual status or demand to the status of the report. To solve the problems, automatic finding incomplete reports and completing missing information are indispensable. In this paper, we propose methods to detect parts related to an actual status or demand to the status in a report using empirical patterns, dependency relations, and several machine learning techniques. Experimental results show that an average F-score and an average accuracy score our methods achieved were 0.798 and 0.893, respectively. In addition, in our methods, RF achieved better results than SVM for both F-score and accuracy scores.. |
| 80. | Yuta Sano, Tsunenori Mine, Extraction of current actual status and demand expressions from complaint reports, 18th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2016 18th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2016 - Proceedings, 10.1145/3011141.3011201, 149-153, 2016.11, Government 2.0 activities have become very attractive and popular these days. Using platforms to support the activities such as FixMyStreet, SeeClickFix, or CitySourced, anyone can anytime report issues or complaints in a city with their photographs and geographical information on the Web, and share them with other people. On the other hand, unlike telephone calls, the concreteness of a report depends on its reporter; the actual status and demand to the status may not be described clearly or either one may be miss-described in the report. It may accordingly happen that officials in the city management section can not understand the actual sta-tus or a demand to the status from the report. To solve the problems, it is indispensable to complement missing in-formation and estimate the actual status or the demand to the status from ambiguous information in the report. This paper proposes novel methods to detect segments related to an actual status and the demand to the status in a report. The methods combine empirical rules with several machine learning techniques that actively use dependency relation between words. Experimental results illustrate the validity of the proposed methods.. |
| 81. | Shaymaa E. Sorour, Shaymaa Abd El Rahman, Tsunenori Mine, Teacher interventions to enhance the quality of student comments and their effect on prediction performance, 46th Annual Frontiers in Education Conference, FIE 2016 FIE 2016 - Frontiers in Education 2016 The Crossroads of Engineering and Business, 10.1109/FIE.2016.7757736, 2016.11, Today, the use of learning analytics is becoming more crucial in the learning environment for the purpose of understanding and optimizing students' learning situations. The purpose of this paper is to examine the impacts of Teacher Interventions (TIs) on students' attitudes and achievements involved with the lesson by analyzing their freestyle comment data after every lesson. The current study proposes a new method for building an accessible prediction model, which represents students' activities, situations and viewpoints; the method classifies words in the student comments into six attribute types and indicates the most important types that affect the prediction results. Further, the prediction results are compared with the topic-based statistical method that uses Latent Dirichlet Allocation and Support Vector Machine models. The results proved that there were positive correlations between TIs and the quality of writing comments that affect on improving the prediction results.. |
| 82. | Shaymaa E. Sorour, Shaimaa Abd El Rahman, Samir A. Kahouf, Tsunenori Mine, Understandable prediction models of student performance using an attribute dictionary, 15th International Conference on Advances in Web-Based Learning, ICWL 2016 Advances in Web-Based Learning - ICWL 2016 - 15th International Conference, Proceedings, 10.1007/978-3-319-47440-3_18, 161-171, 2016.10, This paper proposes a new approach for predicting final student grade with high accuracy. It builds an attribute dictionary (AD) automatically from students’ comments collected after every lesson. Furthermore, it combines white-box models: Decision Tree (DT) and Random Forest (RF), and a black-box model: Support Vector Machine (SVM) to construct an interpretable prediction model and carry out eclectic rule-extraction. First, the AD is built from students’ comments, which are converted to attribute vectors. Second, the output decision is generated by SVM using the attribute vectors in the training phase and then DT and RF are applied to the output decision to extract symbolic rules. Experimental results illustrate the validity of the AD constructed automatically and the superiority of the proposed approach compared to single machine learning techniques: DT, RF and SVM.. |
| 83. | Mansur As, Tsunenori Mine, Empirical study of travel time variability using bus probe data, 1st IEEE International Conference on Agents, ICA 2016 Proceedings - 2016 International Conference on Agents, ICA 2016, 10.1109/ICA.2016.31, 146-149, 2016.09, Estimation of bus travel time is one of crucial issues for passengers to let them know their departure time and arrival time at the destination, and to reduce their waiting time at the bus stop. Furthermore, it can also help to promote the development of city public transportation. To estimate bus travel time, it is worth of knowing whether target routes for passenger's travel is unstable or not, i.e. route with frequent delay or not. In this paper, we present an approach of distinguishing stable and unstable routes using bus probe data. The approach includes two phases; first phase estimates travel time variabilities on routes of a day, and second one distinguishes stable and unstable routes. We divide a day into eight inter-time periods: early morning, morning peak, late morning, midday, early afternoon, afternoon peak, evening, and late night, and detect stable and unstable routes considering the variabilities of standard deviation of the routes in a day. We used bus probe data collected from November 21st to December 20th in 2013. Considering the overall distribution of standard deviation of average travel time of all routes, we defined the criterion to distinguish stable and unstable routes and found the rate of unstable routes on weekends tended to become more than that on weekdays.. |
| 84. | Kenji Hisazumi, Tsuneo Nakanishi, Shota Ishibashr, Go Hirakawa, Tsunenori Mine, Takahiro Ando, Hiroki Furusw, Akira Fukuda, Operation phase metrics for smart mobility platform, 1st IEEE International Conference on Agents, ICA 2016 Proceedings - 2016 International Conference on Agents, ICA 2016, 10.1109/ICA.2016.25, 150-153, 2016.09, This paper identifies metrics that can be used in the operation phase to realize a platform to facilitate the development of services for smart mobility. The paper analyzes requirements of the platform forsmart mobility using the I∗ framework which facilitates identification of goals between stakeholders. We conduct goal-question-metric(GQM) identifying metrics, which can evaluate whether the application or platform meets the goals that we have identified through the I∗ analysis.. |
| 85. | Haibo Yu, Wenhao Song, Tsunenori Mine, APIBook - An effective approach for finding APIs, 8th Asia-Pacific Symposium on Internetware, Internetware 2016 8th Asia-Pacific Symposium on Internetware, Internetware 2016 - Proceedings, 10.1145/2993717.2993727, 45-53, 2016.09, Software libraries have become more and more complex in recent years. Developers usually have to rely on search engines to find API documents and then select suitable APIs to do relevant development when working on unfamiliar functions. However, the traditional search engines do not focus on searching APIs that make this process inconvenient and time consuming. Although a lot of efforts have been made on API understanding and code search in industry and academia, work and tools that can recommend API methods to users based on their description of API's functionality are still very limited. In this paper, we propose a search-based recommendation algorithm on API methods. We call the algorithm APIBook and implement an API method recommendation tool based on the proposed algorithm. The algorithm can recommend relevant API methods to users based on user input written in natural language. This algorithm combines semantic relevance, type relevance and the extent of degree that API method is used to sort these API methods and rank those that are highly relevant and widely used in the top positions. Examples of codes in real projects are also provided to help users to learn and to understand the API method recommended. The API recommendation tool selects the Java Standard Library as well as 100 popular open source libraries as API recommending material. Users can input the API description via the Web interface, and view the search results with sample codes on screen. The evaluation experiment is performed and the result shows that APIBook is more effective for finding APIs than traditional search models and it takes on average 0.7 seconds for finding relevant API methods which we think to be reasonable for satisfying daily query requirements.. |
| 86. | Shaymaa E. Sorour, Tsunenori Mine, Building an interpretable model of predicting student performance using comment data mining, 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016 Proceedings - 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016, 10.1109/IIAI-AAI.2016.114, 285-291, 2016.07, Most current prediction models are difficult for teachers to interpret. This induces significant problems of grasping characteristics for each grade group of students, which are helpful for giving intervention and providing feedback to them. In this paper, we propose a new method to build a practical prediction model based on comment data mining. The current study classifies students' comments into six attributes (attitudes, finding, cooperation, review the lesson, understanding, and next activity plan), then extracts generic rules 'IF-THEN' about students' activities, attitudes and situations in the learning environment. Decision Tree (DT) and Random Forest (RF) models are applied to discriminate unique features related to each grade group. Evaluation results reported a set of rules for students' performance among with their situations reflected through all the course of a semester.. |
| 87. | Hiroyuki Nakamura, Shiro Mise, Tsunenori Mine, Personalized recommendation for public transportation using user context, 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016 Proceedings - 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016, 10.1109/IIAI-AAI.2016.204, 224-229, 2016.07, This paper presents a new application of public transit guide system named PATRASH (Personalized Autonomous TRAansit recommendation System considering user context and History). Although existing transit guide systems provide a lot of functions, their users can not always use all the functions under their control because of the complexity of the functions. Under this situation, we developed and supply PATRASH to reduce complicated user operations. PATRASH provides simple functions users can easily use. The concept of PATRASH is "First Show, Second Search." PATRASH displays routes and time table information recommended to the users. If they need, they can search another route. The target users of PATRASH are transit riders who come to Ito campus of Kyushu university. Ito campus locates in a rural area and has four routes run by three bus transportation companies and connected to a railroad or a subway. Since the main route usually used by each transit rider seems to be almost determined, we believe personalized function of PATRASH becomes more and more important. To realize the concept of PATRASH and give simple usability to the users, we propose a new 3D adaptive interface and release PATRASH to the public. We also present a preliminal case study of PATRASH project.. |
| 88. | Akira Fukuda, Hisazumi Kenji, Shigemi Ishida, Tsunenori Mine, Tsuneo Nakanishi, Hiroki Furusho, Shigeaki Tagashira, Yutaka Arakawa, Kunihiko Kaneko, Weiqiang Kong, Towards sustainable information infrastructure platform for smart mobility - Project overview, 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016 Proceedings - 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016, 10.1109/IIAI-AAI.2016.110, 211-214, 2016.07, Smart mobility systems, which include Intelligent Transportation System (ITS) and smart energy systems, become more important. There is, however, lack of its platform studies. This paper proposes a sustainable information infrastructure project for smart mobility systems. The project pursues issues that establish an information infrastructure architecture and seamless development method chain for it. The project has mainly two features, 1) applying life-cycle-oriented methods, which are a cycle from system development to operations, to the real world, and 2) dealing with uncertainties when a system begins to be designed. This paper describes an overview of the project.. |
| 89. | Shaymaa E. Sorour, Tsunenori Mine, Exploring students' learning attributes in consecutive lessons to improve prediction performance, Australasian Computer Science Week Multiconference, ACSW 2016 Proceedings of the Australasian Computer Science Week Multiconference, ACSW 2016, 10.1145/2843043.2843066, 2016.02, Building an understandable student prediction model has an essential role to play in the educational environment. Most current prediction models are difficult for teachers to interpret. This poses problems for model use (e.g., improve student performance, interventions and allow a feedback process). In this paper, we propose a new approach in building a practical model by identifying a number of attributes in comment data that reflect students' learning attitudes, tendencies and activities involved with the lesson. We check the capability of an attributes representation model compared to the Latent Dirichlet Allocation (LDA) model that represents student comments as a statistical latent class 'Topics.' In addition, we employ a Multi-Instance Learning (MIL) method to all available information for each student to improve the efficiency and effectiveness of classical representation for each lesson to predict final student performance. Computational experiments show that when the model is regarded as MIL, the prediction performance achieves better results than those based on single instance representation for each lesson.. |
| 90. | Yuta Sano, Kohei Yamaguchi, Tsunenori Mine, Automatic Classification of Complaint Reports about City Park, International Institute of Applied Informatics, 1, 4, 119-130, 2015.12. |
| 91. | Shaymaa E. Sorour, Kazumasa Goda, Tsunenori Mine, Evaluation of effectiveness of time-series comments by using machine learning techniques, Journal of Information Processing, 10.2197/ipsjjip.23.784, 23, 6, 784-794, 2015.11, Understanding individual students more deeply in the class is the most vital role in educational situations. Using comment data written by students after each lesson helps in the understanding of their learning attitudes and situations. They can be a powerful source of data for all forms of assessment. The PCN method categorizes the comments into three items: P (Previous learning activity), C (Current learning activity), and N (Next learning activity plan). The objective of this paper is to investigate how the three time-series items: P, C, and N, and the difficulty of a subject affect the prediction results of final student grades using two types of machine learning techniques: Support Vector Machine (SVM) and Artificial Neural Network (ANN). The experiment results indicate that the students described their current activities (C-comment) in more detail than previous and next activities (P-and N-comments) this tendency is reflected in prediction accuracy and F-measure of their grades.. |
| 92. | Tsunenori Mine, Editor’s message to special issue on e-service and knowledge management toward smart computing society, Journal of Information Processing, 10.2197/ipsjjip.23.744, 23, 6, 744, 2015.11. |
| 93. | Shaymaa E. Sorour, Kazumasa Goda, Tsunenori Mine, Evaluation of effectiveness of time-series comments by using machine learning techniques, Journal of information processing, 10.2197/ipsjjip.23.784, 23, 6, 784-794, 2015.11, Understanding individual students more deeply in the class is the most vital role in educational situations. Using comment data written by students after each lesson helps in the understanding of their learning attitudes and situations. They can be a powerful source of data for all forms of assessment. The PCN method categorizes the comments into three items: P (Previous learning activity), C (Current learning activity), and N (Next learning activity plan). The objective of this paper is to investigate how the three time-series items: P, C, and N, and the difficulty of a subject affect the prediction results of final student grades using two types of machine learning techniques: Support Vector Machine (SVM) and Artificial Neural Network (ANN). The experiment results indicate that the students described their current activities (C-comment) in more detail than previous and next activities (P-and N-comments); this tendency is reflected in prediction accuracy and F-measure of their grades.. |
| 94. | Shaymaa E. Sorour, Jingyi Luo, Kazumasa Goda, Tsunenori Mine, Correlation of grade prediction performance with characteristics of lesson subject, 15th IEEE International Conference on Advanced Learning Technologies, ICALT 2015 Proceedings - IEEE 15th International Conference on Advanced Learning Technologies Advanced Technologies for Supporting Open Access to Formal and Informal Learning, ICALT 2015, 10.1109/ICALT.2015.24, 247-249, 2015.09, Learning analytics is valuable sources of understanding students' behavior and giving feedback to them so that we can improve their learning activities. Analyzing comment data written by students after each lesson helps to grasp their learning attitudes and situations. They can be a powerful source of data for all forms of assessment. In the current study, we break down student comments into different topics by employing two topic models: Probabilistic Latent Semantic Analysis (PLSA), and Latent Dirichlet Allocation (LDA), to discover the topics that help to predict final student grades as their performance. The objectives of this paper are twofold: First, determine how the three time-series items: P-, C- and N-comments and the difficulty of a subject affect the prediction results of final student grades. Second, evaluate the reliability of predicting student grades by considering the differences between prediction results of two consecutive lessons. The results obtained can help to understand student behavior during the period of the semester, grasp prediction error occurred in each lesson, and achieve further improvement of the student grade prediction.. |
| 95. | Hiroyuki Nakamura, Yuan Gao, He Gao, Hongliang Zhang, Akifumi Kiyohiro, Tsunenori Mine, Adaptive User Interface for Personalized Transportation Guidance System, Springer-Verlag Berlin and Heidelberg GmbH \& Co. KG, 90, 119-134, 2015.07. |
| 96. | Yuta Sano, Kohei Yamaguchi, Tsunenori Mine, Category Estimation of Complaint Reports about City Park, 4th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2015 Proceedings - 2015 IIAI 4th International Congress on Advanced Applied Informatics, IIAI-AAI 2015, 10.1109/IIAI-AAI.2015.195, 61-66, 2015.07, A lot of actions have recently been taken to support Government 2.0 movement. As the number of the actions increase, many people submit greater number of complaint reports by phone or mobile devices, and make sure the situation reported with each other. According to the actions, the delay in taking action of the government side becomes more clearly identified due to overloads of the government side to deal with the activities. To remedy the above situations, it increases of importance to develop an efficient approach to deal with the complaint reports. Automatic classification of the complaint reports, or estimation and extraction of demanding sentences from the reports are contributory to the approach. In this paper, we propose a method of automatically estimating categories of the complaint reports as a first step. We conducted experiments of estimating categories of the complaint reports. The experiment results showed the following findings: (1) Feature selection is a key to improve the F-score of estimating categories of complaint reports. The percentage of the words strongly effective for the category estimation is about 3.9% of the entire distinct words. (2) Proposed Mutual-Information-based methods outperform the F-score of a conventional Random-Forest-based method. (3) The F-score performance of estimating a category depends on the ambiguity level of the category. In particular, the F-score of estimating categories of a complaint report assigned multiple categories is 1.5 times worse than that of a complaint report assigned single category.. |
| 97. | Shaymaa E. Sorour, Kazumasa Goda, Tsunenori Mine, Estimation of Student Performance by Considering Consecutive Lessons, 4th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2015 Proceedings - 2015 IIAI 4th International Congress on Advanced Applied Informatics, IIAI-AAI 2015, 10.1109/IIAI-AAI.2015.170, 121-126, 2015.07, Examining student learning behavior is one of the crucial educational issues. In this paper, we propose a new method to predict student performance by using comment data mining. A teacher just asks students after every lesson to freely describe and write about their learning situations, attitudes, tendencies, and behaviors. The method employs Latent Dirichlet Allocation (LDA) and Support Vector Machine (SVM) to predict student grades in each lesson. In order to obtain further improvement of prediction results, we apply a majority vote method to the predicted results obtained in consecutive lessons to keep track of each student's learning situation. Also, we evaluate the reliability of the predicted student grades to know when we can rely prediction results of student grade during the period of the semester. The experiment results show that our proposed method continuously tracked student learning situation and improved prediction performance of final student grades compared to Probabilistic Latent Semantic Analysis (PLSA) and Latent Semantic Analysis (LSA) models. Also, considering the differences of prediction results in the two consecutive lessons helps to evaluate the reliability of the predicted results.. |
| 98. | Tsunenori Mine, Message from Program Chair, Proceedings - 2015 IIAI 4th International Congress on Advanced Applied Informatics, IIAI-AAI 2015, 10.1109/IIAI-AAI.2015.153, xviii, 2015.07. |
| 99. | Masaki Maruta, Yuta Sano, Kohei Yamaguchi, Tsunenori Mine, Visitor Behavior Analysis Based on Large-Scale Wi-Fi Location Data, 4th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2015 Proceedings - 2015 IIAI 4th International Congress on Advanced Applied Informatics, IIAI-AAI 2015, 10.1109/IIAI-AAI.2015.194, 55-60, 2015.07, The paper aims to interpret visitor behaviors by analyzing a large scale Wi-Fi location data obtained at Interop Tokyo 2014. We first detected a situation of a visitor's stay at a booth, calculated the sojourn time of the visitor and represented each visitor as a booth vector whose element value is the total sojourn time of the visitor at a booth. Then, we classified the visitors by k-Means. By using category labels of each booth, we analyzed characteristics of clusters. The results illustrate that some categories appear at the top rank of most clusters, and the area of the booths included in each cluster is mostly some specific small one, not the entire one.. |
| 100. | Shaymaa Sorour, Tsunenori Mine, Kazumasa Goda, Sachio Hirokawa, A Predictive Model to Evaluate Students Performance, Journal of Information Processing, 10.2197/ipsjip.23.192, 23, 2, 192-201, 2015.02, [URL]. |
| 101. | Shaymaa E. Sorour, Kazumasa Goda, Tsunenori Mine, Correlation of topic model and student grades using comment data mining, 46th SIGCSE Technical Symposium on Computer Science Education, SIGCSE 2015 SIGCSE 2015 - Proceedings of the 46th ACM Technical Symposium on Computer Science Education, 10.1145/2676723.2677259, 441-446, 2015.02, Assessment of learning progress and learning gain play a pivotal role in education fields. New technologies like comment data mining promote the use of new types of contents; student comments highly reflect student learning attitudes and activities compared to more traditional methods and they can be a powerful source of data for all forms of assessment. A teacher just asks students after every lesson to freely describe and write about their learning situations and behaviors. This paper proposes new methods based on a statistical latent class "Topics" for the task of student grade prediction; our methods convert student comments using latent semantic analysis (LSA) and probabilistic latent semantic analysis (PLSA), and generate prediction models using support vector machine (SVM) and artificial neural network (ANN) to predict student final grades. The experimental results show that our methods can accurately predict student grades based on comment data.. |
| 102. | Shaymaa E. Sorour, Tsunenori Mine, Kazumasa Goda, Sachio Hirokawa, Predicting students' grades based on free style comments data by artificial neural network, Proceedings - Frontiers in Education Conference, FIE, 10.1109/FIE.2014.7044399, 2015-, February, 2015.02, Predicting students' academic achievement with high accuracy has an important vital role in many academic disciplines. Most recent studies indicate the important role of the data type selection. They also attempt to understand individual students more deeply by analyzing questionnaire for a particular purpose. The present study uses free-style comments written by students after each lesson, to predict their performance. These comments reflect their learning attitudes to the lesson, understanding of subjects, difficulties to learn, and learning activities in the classroom. To reveal the high accuracy of predicting student's grade, we employ (LSA) latent semantic analysis technique to extract semantic information from students' comments by using statistically derived conceptual indices instead of individual words, then apply (ANN) artificial neural network model to the analyzed comments for predicting students' performance. We chose five grades instead of the mark itself to predict student's final result. Our proposed method averagely achieves 82.6% and 76.1% prediction accuracy and F-measure of students' grades, respectively.. |
| 103. | Shaymaa E. Sorour, Kazumasa Goda, Tsunenori Mine, Correlation of topic model and student grades using comment data mining, SIGCSE 2015 - Proceedings of the 46th ACM Technical Symposium on Computer Science Education, 10.1145/2676723.2677259, 441-446, 2015.02, Assessment of learning progress and learning gain play a pivotal role in education fields. New technologies like comment data mining promote the use of new types of contents student comments highly reflect student learning attitudes and activities compared to more traditional methods and they can be a powerful source of data for all forms of assessment. A teacher just asks students after every lesson to freely describe and write about their learning situations and behaviors. This paper proposes new methods based on a statistical latent class "Topics" for the task of student grade prediction our methods convert student comments using latent semantic analysis (LSA) and probabilistic latent semantic analysis (PLSA), and generate prediction models using support vector machine (SVM) and artificial neural network (ANN) to predict student final grades. The experimental results show that our methods can accurately predict student grades based on comment data.. |
| 104. | Shaymaa E. Sorour, Tsunenori Mine, Kazumasa Goda, Sachio Hirokawa, A predictive model to evaluate student performance, Journal of information processing, 10.2197/ipsjjip.23.192, 23, 2, 192-201, 2015.01, In this paper we propose a new approach based on text mining techniques for predicting student performance using LSA (latent semantic analysis) and K-means clustering methods. The present study uses free-style comments written by students after each lesson. Since the potentials of these comments can reflect student learning attitudes, understanding of subjects and difficulties of the lessons, they enable teachers to grasp the tendencies of student learning activities. To improve our basic approach using LSA and k-means, overlap and similarity measuring methods are proposed. We conducted experiments to validate our proposed methods. The experimental results reported a model of student academic performance predictors by analyzing their comments data as variables of predictors. Our proposed methods achieved an average 66.4% prediction accuracy after applying the k-means clustering method and those were 73.6% and 78.5% by adding the overlap method and the similarity measuring method, respectively.. |
| 105. | Hiroyuki Nakamura, Yuan Gao, He Gao, Hongliang Zhang, Akifumi Kiyohiro, Tsunenori Mine, Adaptive user interface for personalized transportation guidance system, Intelligent Systems Reference Library, 10.1007/978-3-662-47227-9_9, 90, 119-134, 2015.01, Public transportation guidance services, such asYahoo, Jorudan andNAVITIME, are widely used nowadays and support our daily lives. Although they provide useful services, they have not fully been personalized yet. This paper presents a personalized transportation system called PATRASH: Personalized Autonomous TRAnsportation recommendation System considering user context and History. In particular,we discuss anAdaptiveUser Interface (AUI) of PATRASH.Before designing a personalized route recommendation function for PATRASH’s AUI, we investigated possibilities and effectiveness of the function. First, we collected and analyzed 10 subjects’ usage histories of public transportation. Through this investigation, we confirmed the possibilities and effectiveness of the personalized route recommendation function. Second, we investigated the effectiveness of the basic functions of PATRASH’s AUI by comparing with two major transportation guidance systems in Japan. We evaluated those systems from the point of view of usabilities: click costs and time costs. The experimental results illustrate the effectiveness of AUI of PATRASH.. |
| 106. | Shaymaa E. Sorour, Kazumasa Goda, Tsunenori Mine, Student performance estimation based on topic models considering a range of lessons, 17th International Conference on Artificial Intelligence in Education, AIED 2015 Artificial Intelligence in Education - 17th International Conference, AIED 2015, Proceedings, 10.1007/978-3-319-19773-9_117, 790-793, 2015.01, This paper proposes a prediction framework for student performance based on comment data mining. Given the comments containing multiple topics, we seek to discover the topics that help to predict final student grades as their performance. To this end, the paper proposes methods that analyze students’ comments by two topic models: Probabilistic Latent Semantic Analysis (PLSA), and Latent Dirichlet Allocation (LDA). The methods employ Support Vector Machine (SVM) to generate prediction models of final student grades. In addition, Considering the student grades predicted in a range of lessons can deal with prediction error occurred in each lesson, and achieve further improvement of the student grade prediction.. |
| 107. | Shaymaa Sorour, Tsunenori Mine, Kazumasa Goda, Sachio Hirokawa, Comment Data Mining for Student Grade Prediction Considering Differences in Data for Two Classes, The International Association for Computer and Information Science (ACIS), 15, 2, 12-25, 2014.12, [URL]. |
| 108. | Shaymaa E. Sorour, Tsunenori Mine, Kazumasa Godaz, Sachio Hirokawa, Comments data mining for evaluating student's performance, 3rd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2014 Proceedings - 2014 IIAI 3rd International Conference on Advanced Applied Informatics, IIAI-AAI 2014, 10.1109/IIAI-AAI.2014.17, 25-30, 2014.09, The present study proposes prediction approaches of student's grade based on their comments data. Students describe their learning attitudes, tendencies and behaviors by writing their comments freely after each lesson. The main difficulty of this research is to predict students' performance by separately using two class data in each lesson. Although students learn the same subject, there exist differences between the comments in the two classes. The proposed methods basically employ latent semantic analysis (LSA) and two types of machine learning technique: SVM (support vector machine) and ANN (artificial neural network) for predicting students' final results in four grades of S, A, B and C. Moreover, an overlap method was proposed to improve the accuracy prediction results, the method allows to accept two grades for one mark to get the correct relation between LSA results and students' grades. The proposed methods achieve 50.7% and 48.7% prediction accuracy of students' grades by SVM and ANN, respectively. To this end, the results of this study reported models of students' academic performance predictors that are valuable sources of understanding students' behavior and giving feedback to them so that we can improve their learning activities.. |
| 109. | Hiroyuki Nakamura, Yuan Gao, He Gao, Hongliang Zhang, Akifumi Kiyohiro, Tsunenori Mine, Adaptive user interface agent for personalized public transportation recommendation system PATRASH, 17th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2014 PRIMA 2014 Principles and Practice of Multi-Agent Systems - 17th International Conference, Proceedings, 238-245, 2014.01, Public transportation guidance services, which are widely used nowadays, support our daily lives. However they have not fully been personalized yet. Regarding personalized services, an adaptive user interface plays a crucial role. This paper presents an Adaptive User Interface (AUI) agent of our personalized transportation recommendation system called PATRASH. To design and implement the agent, first, we collected and analyzed public transportation usage histories of 10 subjects so as to confirm the possibilities and effectiveness of the personalized route recommendation function. Then we propose a method to deal with user histories and evaluate the effectiveness of the proposed method based on click costs, comparing with two major transportation guidance systems in Japan. We also propose a decision-tree-based route recommendation method. The experimental results illustrate the effectiveness of the proposed method.. |
| 110. | Akifumi Kiyohiro, Kohei Yamaguchi, He Gao, Hiroyuki Nakamura, Tsunenori Mine, Customer behavior analysis on after getting off the train based on usage histories of smart IC card, 3rd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2014 Proceedings - 2014 IIAI 3rd International Conference on Advanced Applied Informatics, IIAI-AAI 2014, 10.1109/IIAI-AAI.2014.63, 269-274, 2014.01, Capturing people's behavior patterns, such as purchase patterns or shop-around-behavior patterns, are big marketing concern since such patterns are good resources to invent new marketing services. To this end, a lot of studies using POS (Points Of Sales) data have been conducted to extract purchase behaviors for CRM (Customer Relation Management). In addition, since a lot of widespread sensor devices, smart cards or mobile phones have become available recently, anyone can try to analyze pedestrians' trajectories obtained from GPS data and extract people's behavior patterns. However, only few research has been conducted to analyze relationships between boarding and purchase behaviors based on usage histories of smart IC cards. This paper presents case studies of purchase behavior analysis based on usage histories of smart IC cards, especially focusing on purchase behaviors of passengers who just get off trains.. |
| 111. | Hiroyuki Nakamura, Hongliang Zhang, Yuan Gao, He Gao, Akifumi Kiyohiro, Tsunenori Mine, Dealing with bus delay and user history for personalized transportation recommendation, 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014 Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014, 10.1109/CSCI.2014.74, 410-415, 2014.01, A personalized system considering user context and social histories is attractive. We present a personalized transportation system called PATRASH: Personalized Autonomous Transportation recommendation System considering user context and History. PATRASH considers not only users' context and transportation histories, but also real bus delay. The bus delay returned by Bus Delay API (BDAPI) is used for making adjustments of recommended routes. In this paper, we proposes a model for dealing with the bus delay information. We also make confirmation of effectiveness or possibilities of personalized route recommendation based on user context and histories. To this end, we investigated 10 examinees' usage histories of public transportation as a preliminal case study. The preliminal investigation results promise us to predict individual public transportation route.. |
| 112. | Shaymaa E. Sorour, Tsunenori Mine, Kazumasa Goda, Sachio Hirokawa, Efficiency of LSA and K-means in predicting students' academic performance based on their comments data, 6th International Conference on Computer Supported Education, CSEDU 2014 CSEDU 2014 - Proceedings of the 6th International Conference on Computer Supported Education, 63-74, 2014.01, Predicting students' academic performance has long been an important research topic in many academic disciplines. The prediction will help the tutors identify the weak students and help them score better marks; these steps were taken to improve the performance of the students. The present study uses free style comments written by students after each lesson. These comments reflect their learning attitudes to the lesson, understanding of subjects, difficulties to learn, and learning activities in the classroom. (Goda and Mine, 2011) proposed PCN method to estimate students' learning situations from their comments freely written by themselves. This paper uses C (Current) method from the PCN method. The C method only uses comments with C item that focuses on students' understanding and achievements during the class period. The aims of this study are, by applying the method to the students' comments, to clarify relationships between student's behaviour and their success, and to develop a model of students' performance predictors. To this end, we use Latent Semantic Analyses (LSA) and K-means clustering techniques. The results of this study reported a model of students' academic performance predictors by analysing their comment data as variables of predictors.. |
| 113. | Shaymaa E. Sorour, Tsunenori Mine, Kazumasa Goda, Sachio Hirokawa, Prediction of students' grades based on free-style comments data, 13th International Conference on Advances in Web-Based Learning, ICWL 2014 Advances in Web-Based Learning, ICWL 2014 - 13th International Conference, Proceedings, 10.1007/978-3-319-09635-3_15, 142-151, 2014.01, In this paper we propose a new approach based on text mining technique to predict student's performance using LSA (latent semantic analysis) and K-means clustering method. The present study uses free style comments written by students after each lesson. Since the potentials of these comments can reflect students' learning attitudes, understanding and difficulties to the lessons, they enable teachers to grasp the tendencies of students' learning activities.To improve this basic approach, overlap method and similarity measuring technique are proposed. We conducted experiments to validate our proposed methods. The experimental results illustrated that prediction accuracy was 73.6% after applying the overlap method and that was 78.5% by adding the similarity measuring.. |
| 114. | Hiroyuki Nakamura, Yuan Gao, He Gao, Hongliang Zhang, Akifumi Kiyohiro, Tsunenori Mine, Toward personalized public transportation recommendation system with adaptive user interface, 3rd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2014 Proceedings - 2014 IIAI 3rd International Conference on Advanced Applied Informatics, IIAI-AAI 2014, 10.1109/IIAI-AAI.2014.31, 103-108, 2014.01, Public transportation guidance services, such as Yahoo, Jorudan and NAVITIME, are widely used nowadays and support our daily lives. Although they provide useful services, they have not fully been personalized yet. This paper presents a personalized transportation system called Patrash: Personalized Autonomous TRAnsportation recommendation System considering user context and History. In particular, we discuss an Adaptive User Interface (AUI) of Patrash. Before designing a personalized route recommendation function for Patrash's AUI, we investigated possibilities and effectiveness of the function. First, we collected and analyzed 10 subjects' usage histories of public transportation. Through this investigation, we confirmed the possibilities and effectiveness of the personalized route recommendation function. Second, we investigated the effectiveness of the basic functions of Patrash's AUI by comparing with two major transportation guidance systems in Japan. We evaluated those systems from the points of views of usabilities: click costs and time costs. The experimental results illustrate the effectiveness of AUI of Patrash.. |
| 115. | Tsunenori Mine, Tomoyuki Kakuta, Akira Ono, Reciprocal recommendation for job matching with bidirectional feedback, 2nd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2013 Proceedings - 2nd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2013, 10.1109/IIAI-AAI.2013.91, 39-44, 2013.12, This paper proposes a novel reciprocal recommendation method for job matching with bi-directional feedback. The proposed method uses, as mutual feedback, bilateral messages between job seekers and recruiters, such as applying to a job, scout of a seeker, and reply to the offer, on the seekers-recruiters' user network. During job matching process, user agents, as delegate of their owners, send and receive those messages with each other. From those feedback messages, each user agent computes the popularity degree of its owner user: seeker or recruiter, and evaluation degree of each other from the popularity degree, considering both the popularity and evaluation degrees, and the similarity between a condition provided by its user and a profile of each candidate user, the agent dynamically updates a ranking list for recommendation of its owner user after every matching action. Preliminary experiments illustrate the validity of the proposed method.. |
| 116. | Kazumasa Goda, Sachio Hirokawa, Tsunenori Mine, Correlation of grade prediction performance and validity of self-evaluation comments, 2013 13th ACM SIGITE Annual Conference on Information Technology Education, SIGITE 2013 SIGITE 2013 - Proceedings of the 2013 ACM SIGITE Annual Conference on Information Technology Education, 10.1145/2512276.2512294, 35-42, 2013.11, To grasp a student's lesson attitude and learning situation and to give a feed back to each student are educational foundations. Goda et al. proposed the PCN method to estimate a learning situation from a comment freely written by students[6, 7]. The PCN method categorizes comments into three items of P (previous), C(current) and N(next). They pointed out a correlation between the student's final results and the validity of a descriptive content of item C, that is something related to understanding of the lesson and learning attitudes to the lesson. However, a problem left in their work is the badness of performance in prediction for upper grade students. This paper proposes two manners of utilization of PCN scores: the validity level determination for assessment, and for prediction performance of students' final grades. In order to validate the proposed manners of utilization, we conducted two experiments. First, we employed multiple regression analysis to calculate PCN scores that determine the validity level with respect to each viewpoint. Students who wrote comments with a high PCN score are considered as those who describe their learning attitude appropriately. We also applied a machine learning method SVM (support vector machine) to students' comments for predicting their final results in five grades of S, A, B, C and D. Experimental results illustrated that as comments of students get higher PCN scores, the prediction performance of the students' grades becomes higher.. |
| 117. | Kazumasa Goda, Sachio Hirokawa, Tsunenori Mine, Automated evaluation of student comments on their learning behavior, 12th International Conference on Web-based Learning, ICWL 2013 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10.1007/978-3-642-41175-5_14, 8167 LNCS, 131-140, 2013.10, Learning comments are valuable sources of interpreting student status of understanding. The PCN method introduced in [Gouda2011] analyzes the attitudes of a student from a view point of time series. Each sentence of a comment is manually classified as one of P,C,N or O sentence. P(previous) indicates learning activities before the classtime, C(current) represents understanding or achievements during the classtime, and N(next) means a learning activity plan or goal until next class. The present paper applies SVM(Support Vecotor Machine) to predict the category to which a given sentence belongs. Empirical evaluation using 4,086 sentences was conducted. By selecting feature words of each category, the prediction performance was satisfactory with F-measures 0.8203, 0.7352, 0.8416 and 0.8612 for P,C,N and O respectively.. |
| 118. | Haibo Yu, Tsunenori Mine, Makoto Amamiya, Balance A key factor for the evaluation of semantic web applications, 1st IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012 Proceedings of the 2012 IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012, 10.1109/IIAI-AAI.2012.49, 203-208, 2012.12, Balance is very important in all areas from art down to the details of our daily life. There is no exception in research work especially when we want to develop an application which will be used in the real world. Currently more and more semantic Web applications are emerging. Although there are some researches on the evaluation and benchmarking of semantic Web applications, they mainly focused on the semantic Web technology itself or specific types of applications. The evaluation of general features of Semantic Web applications is not sufficient. In this paper, we will focus on the evaluation of one of the general characteristics - balance of semantic Web applications. An analysis of current semantic Web applications will be given first in order to summarize their statistical features and get some hints for identifying the aspects that are critical for balance evaluation. Then we summarize the main aspects of balance evaluation, and present the key factors for each balance evaluation aspect. Finally, suggestions for future semantic Web application development and evaluation will be made based on the analysis of semantic Web applications and the summarizing of balance evaluation aspects.. |
| 119. | Kousaku Kimura, Satoshi Amamiya, Tsunenori Mine, Makoto Amamiya, A semi-structured overlay network for large-scale peer-to-peer systems, 8th International Workshop on Agents and Peer-to-Peer Computing, AP2PC 2009 Agents and Peer-to-Peer Computing - 8th International Workshop, AP2PC 2009, Revised Selected Papers, 10.1007/978-3-642-31809-2_8, 83-94, 2012.09, Peer-to-peer (P2P) communication and computing frameworks are important for constructing robust large-scale distributed systems. Overlay network systems use distributed hash-table (DHT) to provide scalable and efficient node search capabilities. However, the DHT-based method has a problem for the maintenance cost of dynamically changing large-scale-network, in which nodes are frequently joining and leaving. This paper proposes a novel technique of P2P communication path management. The proposed technique devises a robust semi-structured overlay network called Ordered Tree with Tuft (OTT for short). OTT provides not only efficient node searching, but also low-cost self-maintenance capabilities for the dynamically changing network. In this method, joining and leaving of a node are managed in O(1) with high probability. Furthermore, the proposed OTT-based technique can find and construct a path shorter than that on the normal ordered tree, by setting up bypass links between remote nodes on OTT.. |
| 120. | Haibo Yu, Tsunenori Mine, Makoto Amamiya, Towards user intent based searching, 10th IEEE Int. Conf. on Trust, Security and Privacy in Computing and Communications, TrustCom 2011, 8th IEEE Int. Conf. on Embedded Software and Systems, ICESS 2011, 6th Int. Conf. on Frontier of Computer Science and Technology, FCST 2011 Proc. 10th IEEE Int. Conf. on Trust, Security and Privacy in Computing and Communications, TrustCom 2011, 8th IEEE Int. Conf. on Embedded Software and Systems, ICESS 2011, 6th Int. Conf. FCST 2011, 10.1109/TrustCom.2011.191, 1400-1407, 2011.12, According to user's intent, Broder classified Web queries into three classes: navigational, informational and transactional. However, current search engines do not provide relevant search results based on the user's intent. In this paper, we propose a user intent based searching mechanism (UIBS for short) in order to enable precise discovery of a Web site (for navigational searching) as well as aggregating of their information (for informational searching) and performing further activities (for transactional searching). We first propose a Web site capability description interface for the explicit description of a Web site's capability and a search interface that enables explicit description of user's search intents, preferences, and query on the information. And then we describe the process of the query engine which provides relevant search results based on the user's intent, preferences, and requirements. Finally, a test example is given to show the availability of the proposed UIBS mechanism.. |
| 121. | Protection of Personal Information based on User Preference. |
| 122. | Kazumasa Goda, Tsunenori Mine, Analysis of students' learning activities through quantifying time-series comments, 15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2011 Knowledge-Based and Intelligent Information and Engineering Systems - 15th International Conference, KES 2011, Proceedings, 10.1007/978-3-642-23863-5_16, 154-164, 2011.09, These days, many university teachers are concerned about the increasing number of students whose motivation is declining. Some of them fall into a situation that they cannot recover from by themselves, and require assistance, but they hesitate to call for help. In order to recognize such students quickly and give guidance to them in class, we have collected time-series comments in the classroom and analyzed them. In the analysis, we divided the comments into the three time slots: P (Previous), C (Current), and N (Next), and quantify them so that we can infer the learning behaviors between the previous and the current classes. We call this analysis method the PCN method. The PCN method is useful for grasping students' learning status in the class. Some of our case studies illustrate the validity of the PCN method.. |
| 123. | Kenichi Takahashi, Takanori Matsuzaki, Tsunenori Mine, Kouichi Sakurai, Customized program protection for a user customized data protection framework, 2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011 Proceedings - 2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011, 10.1109/CSAE.2011.5953301, 643-649, 2011.08, Some of Internet services require users to provide their sensitive information such as their name, address, credit card number, and an ID-password pair. In these services, the manner in which the provided information is used is solely determined by the service providers. As a result, even when the manner in which information is used by a service provider appears vulnerable, users have no choice but to allow such usage. Therefore, we have proposed a user customized data protection framework that enables users to select the manner in which their sensitive information is protected. In our framework, a user selects a policy that defines the manner in which his/her information is to be protected and its manner defined by the policy is incorporated into a program. By allowing a service provider to the information provided by a user through the program, the user can protect his/her sensitive information in a manner selected by him/her. This framework works well when existing a manner (protection policy) which is tolerant to the alteration of the program, otherwise, a program alteration might be a concern. Therefore, in this paper, we attempts to protect a customized program by using program obfuscation and sanitizable signature techniques.. |
| 124. | Kenichi Takahashi, Takanori Matsuzaki, Tsunenori Mine, Takao Kawamura, Kazunori Sugahara, Security as a service for user customized data protection, 2nd International Conference on Software Engineering and Computer Systems, ICSECS 2011 Software Engineering and Computer Systems - Second International Conference, ICSECS 2011, Proceedings, 10.1007/978-3-642-22191-0_27, 298-309, 2011.07, Some of Internet services require users to provide their sensitive information such as credit card number, and an ID-password pair. In these services, the manner in which the provided information is used is solely determined by the service providers. As a result, even when the manner in which information is used by a service provider appears vulnerable, users have no choice but to allow such usage. In this paper, we propose a framework that enables users to select the manner in which their sensitive information is protected. In our framework, a policy, which defines the type of information protection, is offered as a Security as a Service. According to the policy, users can incorporate the type of information protection into a program. By allowing a service provider to use their sensitive information through this program, users can protect their sensitive information according to the manner chosen by them.. |
| 125. | Hirotake Kobayashi, Tsunenori Mine, Applying user feedback and query destination learningmethod tomultiple communities - an evaluation, Transactions of the Japanese Society for Artificial Intelligence, 10.1527/tjsai.26.97, 26, 1, 97-106, 2011.01, This paper proposes a novel Peer-to-Peer Information Retrieval (P2PIR) method using user feedback and query-destination-learning. The method uses positive feedback information effectively for getting documents relevant to a query by giving higher score to them. The method also utilizes negative feedback information actively so that other agents can filter it out with itself. Using query-destination-learning, the method can not only accumulate relevant information from all the member agents in a community, but also reduce communication loads by caching queries and their sender-responder agent addresses in the community. Experiments were carried out on both single and multiple communities constructed with multi-agent framework Kodama. The experimental results illustrated that the proposed method effectively increased retrieval accuracy.. |
| 126. | Kazumasa Goda, Tsunenori Mine, PCN Quantifying learning activity for assessment based on time-series comments, 3rd International Conference on Computer Supported Education, CSEDU 2011 CSEDU 2011 - Proceedings of the 3rd International Conference on Computer Supported Education, 2, 419-424, 2011, Learning activity plays important role in enhancing one's knowledge and skill. There are many ways to acquire and extract learning activities of students from their learning information; we focus on comments handwritten in their attendance sheets. It is easy for teachers to collect the sheets every class and for students to write their activities as comments. The sheets consequently provide time-series text data related to students; such the data are treasures because the comments and the questionnaire reflect their learning activities directly and indirectly. We propose a method called a PCN method for quantifying the comments into triple showing inferred learning activities student by student. Case studies illustrate the validity of the PCN method.. |
| 127. | Tetsuya Oishi, Tsunenori Mine, Ryuzo Hasegawa, Hiroshi Fujita, Miyuki Koshimura, Related word extraction algorithm for query expansion - An evaluation, Advances in Practical Multi-Agent Systems, 10.1007/978-3-642-16098-1_3, 33-48, 2010.11, When searching for information a user wants, search engines often return lots of results unintended by the user. Query expansion is a promising approach to solve this problem. In the query expansion research, one of the biggest issues is to generate appropriate keywords representing the user's intention. The Related Word Extraction Algorithm (RWEA) we proposed extracts such keywords for the query expansion. In this paper, we evaluate the RWEA through several experiments considering the types of queries given by the users. We compare the RWEA, Robertson's Selection Value (RSV) which is one of the famous relevance feedback methods, and the combination of RWEA and RSV. The results show that as queries become more ambiguous, the advantage of the RWEA becomes higher. From the points of view of query types, the RWEA is appropriate for informational queries and the combined method is for navigational queries. For both query types, RWEA helps to find relevant information.. |
| 128. | Kentaro Hori, Tetsuya Oishi, Tsunenori Mine, Ryuzo Hasegawa, Hiroshi Fujita, Miyuki Koshimura, Related word extraction from wikipedia for web retrieval assistance, 2nd International Conference on Agents and Artificial Intelligence, ICAART 2010 ICAART 2010 - 2nd International Conference on Agents and Artificial Intelligence, Proceedings, 192-199, 2010.09, This paper proposes a web retrieval system with extended queries generated from the contents of Wikipedia.By using the extended queries, we aim to assist user in retrieving Web pages and acquiring knowledge. To extract extended query items, we make much of hyperlinks in Wikipedia in addition to the related word extraction algorithm. We evaluated the system through experimental use of it by several examinees and the questionnaires to them. Experimental results show that our system works well for user's retrieval and knowledge acquisition.. |
| 129. | Kentaro Hori, Tetsuya Oishi, Tsunenori Mine, Ryuzo Hasegawa, Hiroshi Fujita, Miyuki Koshimura: , RELATEDWORD EXTRACTION FROM WIKIPEDIA FOR WEB RETRIEVAL ASSISTANCE, International Conference on Agents and Artificial Intelligence (ICAART) 2010, 192-199, 2010.01. |
| 130. | Tetsuya Oishi, Tsunenori Mine, Ryuzo Hasegawa, Hiroshi Fujita, Miyuki Koshimura, Related Word Extraction Algorithm for Query Expansion - an Evaluation - , Intr. WS on ACCDS in PRIMA 2009 , 2009.12. |
| 131. | Tsunenori Mine, Hirotake Kobayashi, Applying user feedback and query learning methods to multiple communities, Proceedings of PRIMA 2009, 276-291, 2009.12. |
| 132. | Tsunenori Mine, Hirotake Kobayashi, Applying user feedback and query learning methods to multiple communities, 12th International Conference on Principles of Practice in Multi-Agent Systems, PRIMA 2009 Principles of Practice in Multi-Agent Systems - 12th International Conference, PRIMA 2009, Proceedings, 10.1007/978-3-642-11161-7_19, 276-291, 2009.12, This paper proposes a novel Peer-to-Peer Information Retrieval (P2PIR) method using user feedback and query-learning. The method actively utilizes negative feedback information so that other agents can filter it out when retrieving it. The proposed method effectively increases retrieval accuracy and decreases communication loads required for document retrieval in communities. The experiments were carried out on multiple communities constructed with multi-agent framework Kodama [1]. The experimental results illustrated the validity of our proposed method.. |
| 133. | Haibo Yu, Tsunenori Mine, Makoto Amamiya, Semantic ACP2P information retrieval method, 3rd IEEE International Conference on Secure Software Integration Reliability Improvement, SSIRI 2009 SSIRI 2009 - 3rd IEEE International Conference on Secure Software Integration Reliability Improvement, 10.1109/SSIRI.2009.57, 303-308, 2009.12, In this paper, a Semantic Agent-Community-based Peer-to-Peer information retrieval method called SACP2P method is proposed for reliable community Web information sharing. The evaluation experiment is performed and the result has shown that SACP2P method can aggregate information from different sources published through different methods (including Web content and Web services) and be effectiveness on reducing communication loads in a P2P network.. |
| 134. | Haibo Yu, Tsunenori Mine, Makoto Amamiya, Semantic ACP2P Information Retrieval Method, The Third IEEE International Conference on Secure Software Integration and Reliability Improvement (Student Doctoral Program Papers), 297-302, 2009.07. |
| 135. | Kenichi Takahashi, Yoshiki Mitsuyuki, Tsunenori Mine, Kouichi Sakurai, Makoto Amamiya, Design and implementation of security mechanisms for a hierarchical community-based multi-agent system, 10th Pacific Rim International Conference on Multi-Agents, PRIMA 2007 Agent Computing and Multi-Agent Systems - 10th Pacific Rim International Conference on Multi-Agents, PRIMA 2007, Revised Papers, 10.1007/978-3-642-01639-4_12, 134-145, 2009.07, Recently, several community-based systems have been developed; however, almost all such systems have been developed as Webserver- based systems. Thus, server administrator can easily eavesdrop on user communications, since they have to send/receive information through the server. Therefore, we propose multi-agent-based peer-topeer (P2P) system wherein each peer manages his/her information and exchanges it with other peers directly. This, thus, resolves the problems posed byWeb-server-based systems; however, we have to consider attacks from malicious third parties. This study designs and implements security protocols/mechanisms for a hierarchical community-based multi-agent system. Furthermore, if we consider a practical use case, we should be able to demonstrate that the proposed system can be implemented by combining it with existing security techniques for more reliable and rapid deployment. Finally, we evaluate the performance of the proposed security system and present an example application.. |
| 136. | Tsunenori Mine, Kosaku Kimura, Satoshi Amamiya, Ken'ichi Takahashi, Makoto Amamiya, Agent-Community-Network-Based Secure Collaboration Support System, Agent-Based Technologies and Applications for Enterprise Interoperability -- International Workshops, ATOP 2005, Utrecht, The Netherlands, July 25-26, 2005, and ATOP 2008, Estoril, Portugal, May 12-13, 2008, Revised Selected Papers --, Springer, 234-255, LNBIP 25, 2009.05. |
| 137. | Tsunenori Mine, Akihiro Kogo, Satoshi Amamiya, Makoto Amamiya, Refinement of the ACP2P by Sharing User-Feedbacks and Learning Query-Responder-Agent-Relationships , The 8th International Conference on Autonomous Agents and MultiAgent Systems, 1341-1342, 2009.05. |
| 138. | Haibo Yu, Tsunenori Mine, Makoto Amamiya, Agent-Community-based P2P semantic MyPortal information retrieval system architecture, Journal of Embedded Computing (Selected papers of EUC2005), IOS Press, 3, 1, 63-75, 2009.01. |
| 139. | Tsunenori Mine, Kosaku Kimura, Satoshi Amamiya, Ken'Ichi Takahashi, Makoto Amamiya, Agent-community-network-based secure collaboration support system, International Workshops on Agent-Based Technologies and Applications for Enterprise Interoperability, ATOP 2008 Agent-Based Technologies and Applications for Enterprise Interoperability - International Workshops, ATOP 2005, Utrecht, The Netherlands, July 25-26, 2005, and ATOP 2008, Revised Selected Papers, 10.1007/978-3-642-01668-4_13, 234-255, 2009.01, Community-based collaboration support systems are useful for exchanging information on topics that community members are interested in. Most of them developed so far are based on server-client architecture and provide their services on Web servers. They require special administrative facilities, and ask users to upload their data on the systems. Furthermore, security mechanisms are not often provided for the communities. Considering these problems, we have been developing an Agent-Community-Network-based collaboration support system: in particular, a business-matching support system. Our system requires neither any special administrative facilities nor the need to upload user data to a special server. Furthermore, it supports secure peer-to-peer communication between users. It is implemented with a multi-agent Kodama framework.. |
| 140. | Tsunenori Mine, Akihiro Kogo, Satoshi Amamiya, Makoto Amamiya, Refinement of the ACP2P by sharing user-feedbacks and learning query-responder-agent-relationships, 8th International Joint Conference on Autonomous Agents and Multiagent Systems 2009, AAMAS 2009 8th International Joint Conference on Autonomous Agents and Multiagent Systems 2009, AAMAS 2009, 1100-1101, 2009.01, This paper proposes two methods for improving the retrieval accuracy of the Agent-Community-based Peer-to-Peer information retrieval (ACP2P) method. One uses user feedbacks exchanged in a community. The other uses query-learning methods that make a middle agent to learn query-responder agent relationships. The latter methods are useful not only for improving the retrieval accuracy, but also for reducing communication loads. We conduct several experiments with test collections so that the evaluation can be done in an objective manner. The experimental results illustrate the validity of our proposed methods.. |
| 141. | Noriaki Sakamoto, Mitsuaki Fukase, Tsunenori Mine, Shigeru Kusakabe, Tsuneo Nakanishi, Yoich Omori, Mesbah Uddin Mohammad, Keijiro Araki, Akira Fukuda, Hiroto Yasuura, Teruaki Kitasuka, Large scale business-academia collaboration in master education course, 1st International Conference on Computer Supported Education, CSEDU 2009 CSEDU 2009 - Proceedings of the 1st International Conference on Computer Supported Education, 2, 159-166, 2009, The progress of Information Technology, which is the infrastructure of an advanced information society, is remarkable and has the enormous impact on our daily life. On the other hand, it has been pointed out by the industry in Japan that there is a lack of highly skilled Information and Communication Technology personnel who can lead the next generation. In order to address this issue, the Graduate School of Information Science and Electrical Engineering in Kyushu University has established Social Information System Engineering education course. Since April 2007, we have started practical education program with an objective to foster world class leaders who have extraordinary technical skill, basic knowledge and sense of ethics. This effort is steadily progressing by the collaboration with various companies through Nippon Keidanren with support of Ministry of Education, Culture, Sports, Science and Technology. There have been several findings in 1) Project Based Learning, 2) omnibus courses, 3) long term internship, and 4) curriculum improvements during the planning and execution of this program. This paper describes the content, method, interim result and evaluation of this education course. We also discuss the challenges that need to be resolved.. |
| 142. | Tetsuya Oishi, Shunsuke Kuramoto, Tsunenori Mine, Ryuzo Hasegawa, Hiroshi Fujita, Miyuki Koshimura, A method for query expansion using the related word extraction algorithm, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2008 Proceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2008, 10.1109/WIIAT.2008.308, 41-44, 2008.12, When searching for information a user wants, search engines often return lots of results unintended by the user. Query expansion is a promising approach to solve this problem. In the query expansion research, one of big issues is to generate appropriate keywords representing the user's intention. This paper proposes the related word extraction algorithm (RWEA) which pays attention to the distance between sentences where keywords in the original query appear. The RWEA is based on the idea that a word nearby important words is also important. We conducted several experiments to evaluate the RWEA. The results promise the effectiveness of the RWEA for improving search results.. |
| 143. | Tetsuya Oishi, Yoshiaki Kambara, Tsunenori Mine, Ryuzo Hasegawa, Hiroshi Fujita, Miyuki Koshimura, Personalized search using ODP-based user profiles created from user bookmark, 10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008 PRICAI 2008 Trends in Artificial Intelligence - 10th Pacific Rim International Conference on Artificial Intelligence, Proceedings, 10.1007/978-3-540-89197-0_78, 839-848, 2008.12, When searching for intended pages on the Internet, users often have a hard time to find the pages because the pages do not always come at the higher rank of searched results. The Personalized Search is a promising approach to solve this problem. In the Personalized Search, User Profiles (UPs in short) that represent interests of the users, are well used and often created from personal documents of the users. This paper proposes (1) a method for making UPs based on Open Directory Project (ODP) and shows (2) a Personalized Search system using the UPs made from Book Marks. Some of experimental results illustrate the validity of our method for making the UPs, and show the precision enhancement of this system.. |
| 144. | Kousaku Kimura, Satoshi Amamiya, Tsunenori Mine, Makoto Amamiya, Routing method based on OTT-shaped overlay network - An improvement and evaluation -, Computer Software, 25, 4, 154-166, 2008.12, A multi-agent system that consists of agents distributed in a network requires an application-level routing method using abstract identifiers such as agent names. We have accordingly proposed a routing method based on an Ordered-Tree-with-Tuft-shaped (OTT-shaped) overlay network. The method can maintain the network robustly and at low cost, and also make use of short-cuts between nodes to find shorter paths than those only found by the ordered tree of OTT. However it has a problem that the path-search cost by shortcuts is too expensive to achieve a reasonable success rate. This paper proposes our newly improved method that finds shorter-paths with both reasonable cost and high success rate of path-search by short-cuts and discusses some of experimental results achieved by software simulation. The results illustrate the validity of our proposed method.. |
| 145. | Tsunenori Mine, Kosaku Kimura, Satoshi Amamiya, Ken'Ichi Takahashi, Makoto Amamiya, Agent-community-network-based business matching and collaboration support system, 7th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2008 7th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2008, 1761-1764, 2008.01, Business matching and collaboration support systems are useful, in particular for small-and-medium sized companies. Most of them developed so far are based on the server-client architecture and provide their services on Web servers. They require special administrative facilities, ask users to upload their data for matching between business needs and seeds, and leave to themselves peer-to-peer communication or negotiation between matched companies. Considering these problems, we have been developing an agent-community-network- based business matching and collaboration support system. Our system requires neither any special administrative facilities nor uploading user data to a special server. It furthermore supports secure peer-to-peer communication between users. It is implemented with multi-agent Kodama framework.. |
| 146. | Satoshi Kurihara, Eizo Akiyama, Takayuki Ito, Michita Imai, Atsusi Iwasaki, Akihiko Ohsuga, Tetsuo Ono, Yasuhiko Kitamura, Shigeo Matsubara, Tsunenori Mine, Koichi Moriyama, Introduction to the Special Issue on Agent, Computer Software, 10.11309/jssst.25.4_1, 25, 4, 1-2, 2008.01. |
| 147. | Tetsuo Kinoshita, Makoto Yokoo, Tsunenori Mine, Yasuhiko Kitamura, Toshiharu Sugawara, Takao Terano, Toramatsu Shintani, Akihiko Ohsuga, Jaws Activities and Their Contribution to Agent Research, Computer Software, 10.11309/jssst.25.4_3, 25, 4, 3-10, 2008.01. |
| 148. | Tetsuya Oishi, Shunsuke Kuramoto, Hiroto Nagata, Tsunenori Mine, Ryuzo Hasegawa, Hiroshi Fujita, Miyuki Koshimura, User-schedule-based Web page recommendation, IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007, 10.1109/WI.2007.4427188, 776-779, 2007.12, In web retrieval, it is often the case that the results given by search engines are not just what we want. To solve this problem there have been many studies on improving queries to be submitted to search engines. However, they are still insufficient due to lack of consideration on time information. To remedy this we propose a user-schedule-based web page recommendation method. The method makes use of a user's schedule to make the recommendation suite to his/her requests. In addition, an algorithm for extracting related words is introduced as a key technique in this method. Some preliminary experiments show very promising results in recommending web pages relevant to users requests. We also confirmed that this algorithm outper-forms a method using mutual information.. |
| 149. | Tsunenori Mine, Akihiro Kogo, Makoto Amamiya, ACP2P Agent-community-based peer-to-peer information retrieval - An evaluation, 4th International Workshop on Agents and Peer-to-Peer Computing, AP2PC 2005 Agents and Peer-to-Peer Computing - 4th International Workshop, AP2PC 2005, Revised Papers, 10.1007/11925941_12, 145-158, 2006.12, The Agent-Community-based Peer-to-Peer Information Retrieval (ACP2P) method[1],[2] uses agent communities to manage and look up information of interest to users. An agent works as a delegate of its user and searches for information that the user wants by communicating with other agents. The communication between agents is carried out in a peer-to-peer computing architecture. Retrieving information relevant to a user query is performed with content files which consist of original and retrieved documents, and two histories: a query/retrieved document history and a query/sender agent history. The ACP2P is implemented using the Multi-Agent Kodama framework. In this paper, we present some mathematical aspects of the ACP2P method with respect to the relationships between communication loads and the number of records that are stored both in the two histories and retrieved document content files, and discuss the experimental results, for which illustrate the validity of this approach. The results confirm the mathematical conjectures we presented and show that the two histories are more useful for reducing the communication load than a naive method employing 'multicast' techniques, and lead to a higher retrieval accuracy than the naive method.. |
| 150. | Tsunenori Mine, Akihiro Kogo, Makoto Amamiya, Agent-community based peer-to-peer information retrieval - An evaluation, Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, 10.1145/1160633.1160878, 1323-1325, 2006.12, The Agent-Community-based Peer-to-Peer Information Retrieval (ACP2P) method uses agent communities to manage and look up information of interest to users. An agent works as a delegate of its user and searches for information that the user wants by communicating with other agents. The communication between agents is carried out in a peer-to-peer computing architecture. The ACP2P is implemented using the Multi-Agent Kodama framework. This paper presents how the ACP2P method works in an agent community network and show the experimental results to illustrate the validity of this approach.. |
| 151. | Tsunenori Mine, Akihiro Kogo, Makoto Amamiya, Agent-Community-Based Peer-to-Peer Information Retrieval and Its Evaluation, Systems and Computers in Japan, Wiley Periodicals, Inc., A Wiley Company,, vol.37, no.13, pp.1-10, 2006.11. |
| 152. | Tsunenori Mine, Akihiro Kogo, Makoto Amamiya, Agent-community-based peer-to-peer information retrieval and its evaluation, Systems and Computers in Japan, 10.1002/scj.20625, 37, 13, 1-10, 2006.11, The Agent-Community-based Peer-to-Peer (ACP2P) information retrieval method uses agent communities to manage and look up information of interest to users. An agent works as a delegate of its user and searches for information that the user wants by communicating with other agents. The communication between agents is carried out in a peer-to-peer computing architecture. Retrieving information relevant to a user query is performed with content files which consist of original and retrieved documents, and two histories: a query/retrieved document history and a query/sender agent history. Making use of the histories has a collaborative filtering effect, which gradually creates virtual agent communities, where agents with the same interests stay together. Our hypothesis is that a virtual agent community reduces communication loads necessary to perform a search. As an agent receives more queries, then more links to new knowledge are acquired. From this behavior, a "give-and-take" (or positive feedback) effect for agents seems to emerge. However, we have only shown parts of the effects of reducing communication loads and making "give-and-take" through preliminary experimental results. This paper discusses more detail of experimental results and shows that the two histories help in reducing communication loads among agents, facilitating bidirectional communications between them and thus creating virtual agent communities, where agents with the same interests stay together.. |
| 153. | Haibo Yu, Tsunenori Mine, Makoto Amamiya, A web information retrieval system architecture based on semantic MyPortal, Workshop on the Semantic Desktop - Next Generation Information Management and Collaboration Infrastructure, ISWC 2005 CEUR Workshop Proceedings, 175, 2005.12, In this paper, we mainly focus on a communication mechanism which enables efficient information publishing and sharing among semantic desktops. We propose MyPortal as a "one stop" for all the information relevant to the user and further propose the conceptual architecture of a P2P community Web information retrieval system based on MyPortal. This architecture enables not only precise location of My-Portal instances and their Web resources but also the automatic or semiautomatic integration of hybrid semantic information delivered through Web content and Web services, and it also ensures that the semantics will not be lost during any part of the lifecycle of the information retrieval process.. |
| 154. | Tsunenori Mine, Daisuke Matsuno, Akihiro Kogo, Makoto Amamiya, ACP2P Agent community based peer-to-peer information retrieval, Third International Workshop on Agents and Peer-to-Peer Computing, AP2PC 2004 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10.1007/11574781_6, 62-73, 2005.12, This paper proposes an agent community based information retrieval method, which uses agent communities to manage and look up information related to users. An agent works as a delegate of its user and searches for information that the user wants by communicating with other agents. The communication between agents is carried out in a peer-to-peer computing architecture. In order to retrieve information relevant to a user query, an agent uses two histories: a query/retrieved document history(Q/RDH) and a query/sender agent history(Q/SAH). The former is a list of pairs of a query and retrieved document information, where the queries were sent by the agent itself. The latter is a list of pairs of a query and the address of a sender agent and shows "who sent what query to the agent". This is useful for finding a new information source. Making use of the Q/SAH is expected to have a collaborative filtering effect, which gradually creates virtual agent communities, where agents with the same interests stay together. Our hypothesis is that a virtual agent community reduces communication loads involved in performing a search. As an agent receives more queries, then more links to new knowledge are acquired. From this behavior, a "give and take" (or positive feedback) effect for agents seems to emerge. We implemented this method with Multi-Agent Kodama, and conducted experiments to test the hypothesis. The empirical results showed that the method was much more efficient than a naive method employing 'multicast' techniques only to look up a target agent.. |
| 155. | Haibo Yu, Tsunenori Mine, Makoto Amamiya, Agent-community-based P2P semantic web information retrieval system architecture, International Conference on Embedded and Ubiquitous Computing, EUC 2005 Embedded and Ubiquitous Computing - International Conference EUC 2005, Proceedings, 538-549, 2005.12, In this paper, we propose a conceptual architecture for a personal semantic Web information retrieval system. It incorporates semantic Web, Web service, P2P and multi-agent technologies to enable not only precise location of Web resources but also the automatic or semi-automatic integration of Web resources delivered through Web contents and Web services. In this architecture, the semantic issues concerning the whole lifecycle of information retrieval were considered consistently and the integration of Web contents and Web services is enabled seamlessly.. |
| 156. | Haibo Yu, Tsunenori Mine, Makoto Amamiya, An architecture for personal semantic web information retrieval system - Integrating web services and web contents, 2005 IEEE International Conference on Web Services, ICWS 2005 Proceedings - 2005 IEEE International Conference on Web Services, ICWS 2005, 10.1109/ICWS.2005.23, 329-338, 2005.12, The semantic Web and Web services technologies have provided both new possibilities and challenges to automatic information processing. There are a lot of researches on applying these new technologies to current personal Web information retrieval systems, but no research addresses the semantic issues from the whole life cycle and architecture point of view. Web services provide a new way for accessing Web resources, but until now, they have been managed separately from conventional Web contents resources. In this paper, we point out new system requirements and propose a conceptual architecture for a personal semantic Web information retrieval system. It incorporates semantic Web, Web services and multi-agent technologies to enable not only precise location of Web resources but also the automatic or semi-automatic integration of hybrid Web contents and Web service resources.. |
| 157. | Haibo Yu, Tsunenori Mine, Makoto Amamiya, An architecture for personal semantic web information retrieval system, 14th International World Wide Web Conference, WWW2005 14th International World Wide Web Conference, WWW2005, 10.1145/1062745.1062825, 974-975, 2005.12, The semantic Web and Web service technologies have provided both new possibilities and challenges to automatic information processing. There are a lot of researches on applying these new technologies into current personal Web information retrieval systems, but no research addresses the semantic issues from the whole life cycle and architecture point of view. Web services provide a new way for accessing Web resources, but until now, they have been managed separately from traditional Web contents resources. In this poster, we propose a conceptual architecture for a personal semantic Web information retrieval system. It incorporates semantic Web, Web services and multi-agent technologies to enable not only precise location of Web resources but also the automatic or semi-automatic integration of hybrid Web contents and Web services.. |
| 158. | Haibo Yu, Tsunenori Mine, Makoto Amamiya, Towards automatic discovery of web portals semantic description of web portal capabilities, First International Workshop on Semantic Web Services and Web Process Composition, SWSWPC 2004 Lecture Notes in Computer Science, 3387, 124-136, 2005.09, Due to the problem of information overload, locating relevant Web portals precisely based on user requirements is quite an essential task. As the need for application-to-application communication and interoperability grows, providing Web portal services that satisfy human as well as machine requirements is becoming a new challenge for Web portals. However, a Web portal capability expressing mechanism, which enables the precise location of Web portals as well as the automated discovery and invocation of Web portal services, is lacking. In this paper, we investigate how to incorporate Semantic Web technology with Web service technologies to describe the capabilities of Web portals. We also discuss the possibilities of using these descriptions for discovering and using the distributed existing portal resources.. |
| 159. | Tsunenori Mine, Daisuke Matsuno, Makoto Amamiya, Agent community based peer-to-peer information retrieval, Transactions of the Japanese Society for Artificial Intelligence, 10.1527/tjsai.19.421, 19, 5, 421-428, 2004.12, This paper proposes an agent community based information retrieval method, which uses agent communities to manage and look up information related to users. An agent works as a delegate of its user and searches for information that the user wants by communicating with other agents. The communication between agents is carried out in a peer-to-peer computing architecture. In order to retrieve information related to a user query, an agent uses two histories: a query/retrieved document history(Q/RDH) and a query/sender agent history(Q/SAH). The former is a list of pairs of a query and retrieved documents, where the queries were sent by the agent itself. The latter is a list of pairs of a query and sender agents and shows "who sent what query to the agent". This is useful to find a new information source. Making use of the Q/S AH is expected to cause a collaborative filtering effect, which gradually creates virtual agent communities, where agents with the same interests stay together. Our hypothesis is that a virtual agent community reduces communication loads to perform a search. As an agent receives more queries, then more links to new knowledge are achieved. From this behavior, a "give and take"(or positive feedback) effect for agents seems to emerge. We implemented this method with Multi-Agents Kodama which has been developed in our laboratory, and conducted preliminary experiments to test the hypothesis. The empirical results showed that the method was much more efficient than a naive method employing 'broadcast' techniques only to look up a target agent.. |
| 160. | Tsunenori Mine, Daisuke Matsuno, Akihiro Kogo, Makoto Amamiya, Design and Implementation of Agent Community based Peer-to-Peer Information Retrieval Method, Eighth International Workshop CIA 2004 on Cooperative Information Agents, 3191, 31-46, LNAI volume 3191 Klusch, M.; Ossowski, S.; Kashyap, V.; Unland, R. (Eds.) pp. 31-46, 2004.09. |
| 161. | Tsunenori Mine, Daisuke Matsuno and Makoto Amamiya: Agent-Community-based Peer-to-Peer Information Retrieval(in Japanese), Japanese Society of Artificial Intelligence Journal J-STAGE, http://tjsai.jstage.jst.go.jp/ja/, vol. 19, no. 5, pp. 421--428, 2004. |
| 162. | Tsunenori Mine, Daisuke Matsuno, Akihiro Kogo, Makoto Amamiya, Design and implementation of agent community based peer-to-peer information retrieval method, 8th International Workshop on Cooperative Information Agents, CIA 2004 Cooperative Information Agents VIII - 8th International Workshop, CIA 2004, 31-46, 2004.01, This paper presents an agent community based peer-to-peer information retrieval method called ACP2P method[16] and discusses the experimental results of the method. The ACP2P method uses agent communities to manage and look up information related to users. An agent works as a delegate of its user and searches for information that the user wants by communicating with other agents. The communication between agents is carried out in a peer-to-peer computing architecture. In order to retrieve information relevant to a user query, an agent uses a content file, which consists of retrieved documents and two histories: a query/retrieved document history(Q/RDH) and a query/sender agent history(Q/SAH). The former is a list of pairs of a query and the address of an agent that returned documents relevant to the query. The latter is a list of pairs of a query and the address of a sender agent and shows "who sent what query to the agent". This is useful for finding a new information source. Making use of Q/SAH is expected to have a collaborative filtering effect, which gradually creates virtual agent communities, where agents with the same interests stay together. Our hypothesis is that a virtual agent community reduces communication loads necessary to perform a search. As an agent receives more queries, then more links to new knowledge are acquired. From this behavior, a "give and take"(or positive feedback) effect for agents seems to emerge. We implemented this method with Multi-Agent Kodama, and conducted experiments to test the hypothesis. The experimental results showed that the method employing two histories was much more efficient than a naive method employing 'multicast' techniques only to look up a target agent. Further, making use of Q/SAH facilitates bidirectional communications between agents and thus creates virtual agent communities.. |
| 163. | Tsunenori Mine, Daisuke Matsuno, Koichiro Takaki, Makoto Amamiya, Agent community based peer-to-peer information retrieval, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004, 3, 1484-1485, 2004, This paper proposes an Agent Community based Peer-to-Peer information retrieval method called ACP2P method, which uses agent communities to manage and look up information related to users. An agent works as a delegate of its user and searches for information that the user wants by communicating with other agents. The communication between agents is carried out in a peer-to-peer computing architecture. In order to retrieve information related to a user query, an agent uses a content file, which consists of retrieved documents, and two histories: a query/retrieved document history(Q/RDH) and a query/sender agent history(Q/SAH). We implemented this method with Multi-Agents Kodama, and conducted preliminary experiments to test the hypothesis. The empirical results showed that the method was much more efficient than a naive method employing 'multicast' techniques only to look up a target agent.. |
| 164. | Tarek Helmy, Satoshi Amamiya, Tsunenori Mine, Makoto Amamiya, A new approach of the collaborative user interface agents, 2003 IEEE/WIC International Joint Conference on Intelligent Agent Technology and Web Intelligence, IAT'03 and WI'03 Proceedings - IEEE/WIC International Conference on Intelligent Agent Technology, IAT'03, 147-153, 2003.12, Next generation of information systems will rely on cooperative intelligent agents for playing a fundamental role in actively searching and finding relevant information on behalf of their users in complex and open environments, such as the Internet. User Interface Agents {VIA) are semi-intelligent systems, which help the users to access, manage, share and exchange information. Recently, various researchers have proposed a learning approach towards building such agents and some working prototypes have been demonstrated. Such agents learn by watching over the shoulder of the user and detect patterns and regularities in the user's behavior. We present a new approach of the collaborative VIA that helps the user to retrieve information that is consistent to the user's need. The model provides tools and utilities for the user to manage his/her information repositories with dynamic organization and adaptation views. In order to investigate the performance of the UIA, we carried out several experiments. Through the experiments, the results ensure that the techniques of personalization, clustering the user's preferences, and making use of the preferences promise to achieve more relevant information to the user's queries.. |
| 165. | Guoqiang Zhong, Ken'ichi Takahashi, Satoshi Amamiya, Daisuke Matsuno, Tsunenori Mine, Makoto Amamiya, From Computer Networks to Agent Networks, the Intelligent Systmes and Soft Computing Minitrack in the Decision Technologies for Management, the Thirty-Sixth Hawaii International Conference on System Sciences (HICSS-36),, http://www.hicss.hawaii.edu/diglib.htm, 2003.01. |
| 166. | Kenichi Takahashi, Satoshi Amamiya, Zhong Guoqiang, Daisuke Matsuno, Tsunenori Mine, Makoto Amamiya, Agent Platform Protocol Bring heterogeneous Agent Platform Together, IEEJ Transactions on Electronics, Information and Systems, 10.1541/ieejeiss.123.1503, 123, 8, 1503-1511, 2003.01, Due to the spread of distributed systems, a number of agent systems have been developed. Since most existing multiagent systems implement different agent platforms, it is extremely hard to get heterogeneous agents to work together. In this paper, we introduce a new network protocol called Agent Platform Protocol (APP), which is designed to meet the exact demands of agent interaction over world-wide networks. The most significant contribution of this protocol is that it supports Peer-to-Peer communication among agent platforms and hides the network-level implementation details from agents. To demonstrate its usefulness, APP has been used to realize the interaction between independent agent systems from two projects, JADE and KODAMA. JADE is an agent system in compliance with the FIPA specifications, and KODAMA is an agent system one being developed in our laboratory. The experimental results show that APP can help JADE and KODAMA agents to communicate with each other without getting the agents being aware of he difference in their agent platforms.. |
| 167. | G. Zhong, K. Takahashi, S. Amamiya, D. Matsuno, T. Mine, M. Amamiya, From computer networks to agent networks, 36th Annual Hawaii International Conference on System Sciences, HICSS 2003 Proceedings of the 36th Annual Hawaii International Conference on System Sciences, HICSS 2003, 10.1109/HICSS.2003.1174210, 2003.01, From the 1990s on, one of the most important challenges facing computer science researchers has been the design and construction of software tools to exploit Internet computing. At the same time, the development of agent technology has gone hand in hand with the explosion of the Internet. As worldwide network computing environments become more and more complex, software agents are believed to have the potential to help present and manage the Internet in an autonomous or semi-autonomous way. Yet, to date, a number of fundamental questions about the theory and practice of this new software engineering paradigm have remained unanswered. Here we explore the features that make the agent-based approach such an appealing and evolutionary computational model. In particular, we envision a global agent-based distributed computing architecture that provides a convenient programming abstraction and sufficient transparency. This paper gives a general introduction to the underlying concepts of our research and development both at the level of design philosophy and in practical implementation techniques. It is argued that the shift from computer networks to agent networks is a significant extension of network programming technology because agents are well suited to modeling, designing and implementing scalable, flexible and secure distributed systems over a worldwide computing environment.. |
| 168. | T. Mine, A. Suganuma, T. Shoudai, Categorizing Questions According To A Navigation List For A Web-Based Self-Teaching System: {AEGIS}, CD-ROM Proc. of International Conference on Computers in Education, 1245-1249, pp., 2002.12. |
| 169. | T. Mine, A. Suganuma, T. Shoudai, Categorizing Questions According To A Navigation List For A Web-Based Self-Teaching System : AEGIS, Proceedings of the ICCE 2002, 1245-1249, pp.1245-1249, 2002.12. |
| 170. | Yusuke Nonaka, Sozo Inoue, Katsuhiko Hatano, Tsutomu Harada, Yoshinari Nomura, Mizuho Iwaihara, Tsunenori Mine, Kazuo Ushijima, Development and operation of a document database for university research and education activities, Journal of Systems and Computers in Japan, Vol. 33, No. 10, pp. 41--53 , 2002.10. |
| 171. | A. Suganuma, T. Mine, T. Shoudai, Dynamic Evaluation of both Students' and Questions' Levels for Generating Appropriate Exercises to Students Automatically, Proc. of Knowledge-Based Software Engineering, 80, 325-328, pp.325-328, 2002.09. |
| 172. | T. Mine, S. Lu, M. Amamiya, Discovering Relationship between Topics of Conferences by Filtering, Extracting and Clustering, Proceedings of the the 3rd International Workshop on Natural Language and Information Systems (NLIS2002), pp.205--209, 2002.09. |
| 173. | A. Suganuma, T. Mine, T. Shoudai, Dynamic Evaluation of both Students' and Questions' Levels for Generating Appropriate Exercises to Students Automatically, Proceedings of the 5th Joint Conference on Knowledge-Based Software Engineering (JCKBSE2002), 80, 325-328, pp.325--328, 2002.09. |
| 174. | T. Mine, S. Lu, M. Amamiya, A Text Mining System DIREC: DIscovering Relationships between Keywords by Filtering, Extracting and Clustering, Proceedings of the 5th Joint Conference on Knowledge-Based Software Engineering (JCKBSE2002), 80, 317-320, pp.317--320, 2002.09. |
| 175. | Yusuke Nonaka, Sozo Inoue, Katsuhiko Hatano, Tsutomu Harada, Yoshinari Nomura, Mizuho Iwaihara, Tsunenori Mine, Kazuo Ushijima, Development and operation of a document database for university research and education activities, Systems and Computers in Japan, 10.1002/scj.10043, 33, 10, 41-53, 2002.09, The academic staff research and education activity database of Kyushu University is a document database system which enables each academic staff member to input and update his or her activity report, administrators to maintain the database, and visitors to search and read reports via the Internet. Those databases and user interfaces can handle mixed report formats by storing metadata of formats and constraints. Through an analysis of the update history of the system and e-mail records between users and developers, we confirmed that distributed administration style reduced human work load and that the majority of bugs are confined to small components. © 2002 Wiley Periodicals, Inc. Syst. Comp. Jpn.. |
| 176. | K. Takahashi, G. Zhong, D. Matsuno, S. Amamiya, T. Mine, M. Amamiya, Interoperability between KODAMA and JADE using Agent Platform Protocol, Proceedings of the Agentcities; Challenges in Open Agent Environmnets, pp.90-94, 2002.07. |
| 177. | G. Zhong, K. Takahashi, S. Amamiya, T. Mine, M. Amamiya, KODAMA Project: from Design to Implementation of a Distributed Multi-Agent Syste, Proceedings of the first international joint conference of Autonomous Agents and Multi-agent Systems, pp.43-44, 2002.07. |
| 178. | T. Helmy, S. Amamiya, T. Mine, M. Amamiya, An Agent-oriented Personalized Web Searching System, Proceedings of the Fourth International Bi-Conference on Agent Oriented Information System, pp.113-116, 2002.07. |
| 179. | A. Suganuma, T. Mine, T. Shoudai, Automatic Generating Appropriate Exercises Based on Dynamic Evaluating both Students' and Questions' Levels, Proc. of World Conf. on Educational Multimedia, Hypermedia and Telecommunications, pp.1898-1903, 2002.06. |
| 180. | A. Suganuma, T. Mine, T. Shoudai, Automatic Generating Appropriate Exercises Based on Dynamic Evaluating both Students' and Questions' Levels, Proceedings of the ED-MEDIA 2002--World Conference on Educational Multimedia, Hypermedia & Telecommunications, pp.1898--1903, 2002.06. |
| 181. | G. Zhong, S. Amamiya, K. Takahashi, T. Mine, M. Amamiya, The Design and Application of KODAMA System, IEICE Transactions INF.\& SYST., Vol.E85-D, No.04, pp.637-646, 2002.04. |
| 182. | GQ Zhong, S Amamiya, K Takahashi, T Mine, M Amamiya, The design and implementation of KODAMA system, IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, E85D, 4, 637-646, 2002.04, Agent-based computing has been advocated by many researchers and software developers as a promising and innovative way to model, design and implement complex Web-related applications. KODAMA (Kyushu university Open & Distributed Autonomous MultiAgent) project, which is described in this paper, is our endeavour to advance both the technology and engineering of well-known multiagent systems. In particular, we have noted that software agents might be the potential solution to many problems faced by today's Web. However, building a high-quality, large-scale multiagent system, which can operate in open environments. is a great challenge. So far. we have devoted a lot of effort to design and implement a generic agent architecture, a hierarchical agent community structure, and an independent network communication middleware. To ensure that KODAMA can be used to create Web-agent applications, its network communication performance and a prototype distributed database retrieval system have been tested. The result shows that KODAMA is suitable for developing network-aware applications,. |
| 183. | T. Mine, A. Suganuma, T. Shoudai, Categorizing questions according to a navigation list for a Web-based self-teaching system AEGIS, International Conference on Computers in Education, ICCE 2002 Proceedings - International Conference on Computers in Education, ICCE 2002, 10.1109/CIE.2002.1186203, 1245-1249, 2002.01, With increasing access to the Internet and the wealth of material online, a Web-based self-teaching system has considerable educational value. Accordingly, we developed AEGIS (Automatic Exercise Generator based on the Intelligence of Students), which automatically generates questions whose difficulty level fits the achievement level of a student. However, it was implicitly assumed that all the questions were already categorized according to their subjects. In practice, this is not the case, but it is unreasonable (because of time and cost) to expect teachers to categorize each question into a suitable subject domain. Therefore, we need a method for categorizing questions automatically according to specified teaching concepts. This paper presents an automatic question categorization mechanism according to both a list of teaching concepts, called a Navigation List (NaviList for short), and the meaning of questions. We define an XML tag called a CONCEPT tag, which indicates a concept in a question, and an ontology, which is a hierarchical cluster of concepts. The method uses the tags and the ontology to categorize questions, based on the similarity between each category in a NaviList pre-composed by a teacher and an ontological concept specified by a CONCEPT tag in a question.. |
| 184. | Tsunenori Mine, Shimiao Lu, Makoto Amamiya, Discovering relationships between topics of conferences by filtering, extracting and clustering, 13th International Workshop on Database and Expert Systems Applications, DEXA 2002 Proceedings - 13th International Workshop on Database and Expert Systems Applications, DEXA 2002, 10.1109/DEXA.2002.1045899, 2002-January, 205-209, 2002.01, This paper presents a text mining system that obtains the relationships between the topics of international conferences. The system at first gathers Web pages related to the query 'call for paper' with a search engine and filters out pages irrelevant to the query with SVMs. Next it extracts the topics of conferences and clusters them. Each cluster embodies the relationships between topics and between topics and conferences. The clustered topics are shown through an Explorer-like graphical user interface. The preliminary experimental results promise that the method works not only for obtaining the relationship between topics of conferences, but also for discovering the relationship between any information entities users are interested in.. |
| 185. | T. Mine, H. Fujitani, M. Amamiya, Japanese Information Retrieval Method Using Syntactic and Statistical Information, Proceedings of the 6th Natural Language Processing Pacific Rim Symposium(NLPRS 2001), pp.429-434, 2001.11. |
| 186. | G. Zhong, K. Takahashi, S. Amamiya, T. Mine, M. Amamiya, An Agent-based System for the Next Generation Web, Proceedings of the 2001 Asia-Pacific Symposium on Information and Telecommunication Technologies, pp.36-40, 2001.11. |
| 187. | T. Mine, M. Amamiya, T. Mitamura, Conference Information Management System : Towards a Personal Assistant System, Proceedings of the First Asia-Pacific Conference on Web Intelligence (WI-2001), pp.247--253, 2001.10. |
| 188. | T. Helmy, S. Amamiya, T. Mine, M. Amamiya, Agents Coordination-Based Web Infrastructure for Personalized Web Searching, Proceedings of the International Conference on Artificial Intelligence, 97-103, pp.97-103, 2001.06. |
| 189. | Tsunenori Mine, Makoto Amamiya, Teruko Mitamura, Conference information management system Towards a personal assistant system, 1st Asia-Pacific Conference on Web Intelligence, WI 2001 Web Intelligence: Research and Development - 1st Asia-Pacific Conference, WI 2001, Proceedings, 2198, 247-253, 2001, We are aiming to develop a personal assistant system which handles its user’s files stored in his/her computers and his/her interesting information that can be accessed on the Web. The system categorizes the files and Web pages gathered and extracts information specified by him/her and stores it into a structured database for use as the knowledge of its dialogue module. This paper presents a prototype of the system that handles information about conferences of interest to the user. The system extracts conference names, submission deadlines, dates, URIs and locations from e-mail messages the user has received, and web pages gathered by both crawling and meta-search. Extracted information is stored into a database so that the user can interactively search conference information via a user interface with natural language queries.. |
| 190. | T. Mine, A. Suganuma, T. Shoudai, The Design and Implementation of Automatic Exercise Generator with Tagged Documents based on the Intelligence of Students:AEGIS, Proc. International Conference on Computers in Education, pp.651-658, 2000.11. |
| 191. | T. Mine, T. Shoudai, A. Suganuma, Automatic Exercise Generator with Tagged Documents Considering Learner's Performance, Proc. World Conference on the WWW and Internet, pp.779-780, 2000.11. |
| 192. | T. Mine, T. Shoudai, A. Suganuma, Automatic Exercise Generator with Tagged Documents Considering Lerner's Performance, Proceedings of the WebNet2000, pp.779-780, 2000.11. |
| 193. | T. Mine, A. Suganuma, T. Shoudai, The Design and Implementation of Automatic Exercise Generator with Tagged Documents based on the Intelligence of Students:AEGIS, Proceedings of the ICCE/ICCAI 2000, pp.651-658, 2000.11. |
| 194. | T. Shoudai, A. Suganuma, T. Mine, AEGIS:Automatic Exercise Generator with Tagged Documents based on the Intelligence of Students, Proc. Knowledge-Based Software Engineering, 62, 311-314, pp.311-314, 2000.09. |
| 195. | T. Shoudai, A. Suganuma, T. Mine, AEGIS: Automatic Exercise Generator with Tagged Documents based on the Intelligence of the Students, Proceedings of the Fourth Joint Conference on Knowledge-Based Software Engineering (JCKBSE) 2000, 62, 311-314, pp.311--314, 2000.09. |
| 196. | G. Zhong, T. Mine, T. Helmy, M. Amamiya, The Design and Application of the KODAMA System, Proceedings of the Fourth Joint Conference on Knowledge-Based Software Engineering (JCKBSE) 2000, 62, 43-50, pp.43--50, 2000.09. |
| 197. | T. Helmy, T. Mine, M. Amamiya, Adaptive exploiting User Profile and Interpretation Policy for Searching and Browsing the Web on KODAMA system, Proceedings of the 2nd International Workshop on Natural Language and Information Systems(NLIS 2000),which is one of Eleventh International Workshops on Database and Expert Systems Applications, 120-124, pp.120--124, 2000.09. |
| 198. | H. Fujitani, T. Mine, M. Amamiya, Incorporation of Japanese Information Retrieval Method Using Dependency Relationship into Probabilistic Retrieval, Proceedings of the PRICAI2000, pp.825, 2000.08. |
| 199. | G. Zhong, K. Takahashi, T. Helmy, K. Takaki, T. Mine, S. Kusakabe, M. Amamiya, KODAMA: As a Distributed Multi-Agent System, The 1st International Workshop on Flexible Networking Cooperative Distributed Agents (FNCDA 2000), which is the Seventh International Conference on Parallel and Distributed Systems: Workshops (ICPADS 2000 Workshops), 435-440, pp.435-440, 2000.07. |
| 200. | T. Helmy, T. Mine, G. Zhong, M. Amamiya, Open Distributed Autonomous Multi-Agent Coordination on the Web, The 1st International Workshop on Flexible Networking Cooperative Distributed Agents (FNCDA 2000), which is the Seventh International Conference on Parallel and Distributed Systems: Workshops (ICPADS 2000 Workshops), 461-466, pp.461-466, 2000.07. |
| 201. | G. Zhong, T. Mine, T. Helmy, M. Amamiya, The Design and Implementation of Agent Communication in KODAMA, Proceedings of the 2000 International Conference on Artificial Intelligence (IC-AI'2000), 673-679, pp.673-679, 2000.06. |
| 202. | T. Helmy, T. Mine, G. Zhong, M. Amamiya, A Novel Multi-Agent KODAMA Coordinantion for On-line Searching and Browsing the Web, Proceedings of The Fifth International Conference and Exhibition on The Practical Application of Intelligent Agents and Multi-Agents, pp.335--338, 2000.04. |
| 203. | Tarek Helmy, Tsunenori Mine, Makoto Amamiya, Adaptive exploiting user profile and interpretation policy for searching and browsing the Web on KODAMA system, Proceedings - International Workshop on Database and Expert Systems Applications, DEXA, 10.1109/DEXA.2000.875014, 2000-January, 120-124, 2000.01, The main thrust of the KODAMA research project is an investigation into novel ways of agentifying the Web based on the pre-existing hyper-link structure, and how this community of agents can automatically achieve and update its interpretation policies and cooperate with other agents to retrieve online distributed relevant information on the Web. The paper focuses on the use of the user interface agents in the KODAMA system for personalized information filtering and adapting, and discusses the method to update a user profile and interpretation policies adaptively for the user. This is an ideal and challenging environment for interface agents. The proposed idea is to employ an adaptive autonomous user interface agent that works for satisfying a user's information needs cooperatively with other agents in the KODAMA system, Web page agents and server agents.. |
| 204. | Hiroki Fujitani, Tsunenori Mine, Makoto Amamiya, Incorporation of Japanese information retrieval method using dependency relationship into probabilistic retrieval, 6th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2000 PRICAI 2000, Topics in Artificial Intelligence - 6th Pacific Rim International Conference on Artificial Intelligence, Proceedings, 2000.01. |
| 205. | Guoqiang Zhong, K. Takahashi, T. Helmy, K. Takaki, T. Mine, S. Kusakabe, M. Amamiya, KODAMA As a distributed multi-agent system, 7th International Conference on Parallel and Distributed Systems, ICPADS 2000 Proceedings - 7th International Conference on Parallel and Distributed Systems Workshops, 10.1109/PADSW.2000.884664, 435-440, 2000.01, With the explosion of the Internet, we are evolving a worldwide network computing environment. At this point, the surged challenge is the next evolutionary technology for the Internet-oriented applications. A KODAMA (Kyushu university Open and Distributed Autonomous Multi-Agent) system is deployed for this demand. KODAMA system can interconnect disparate and distributed agents together to solve some problem whose solution is typically beyond any singular agent's capabilities. The key aspects of KODAMA agents are their autonomy, collaboration, flexibility, as well as stability. To obtain all these features, an appropriate scheme of collaboration among agents is clearly critical. Our new approach focuses on both raising the level of abstraction at which agents cooperate with each other, and hiding the implementation details of communications from agents.. |
| 206. | T. Helmy, T. Mine, Guoqiang Zhong, M. Amamiya, Open distributed autonomous multi-agent coordination on the Web, 7th International Conference on Parallel and Distributed Systems, ICPADS 2000 Proceedings - 7th International Conference on Parallel and Distributed Systems Workshops, 10.1109/PADSW.2000.884668, 461-466, 2000.01, Agent technology is becoming more prevalent as the availability of network access, and the demand for the end uses of agents becomes greater. Intelligent agents for information filtering and retrieval applications and tools are being employed in a variety of ways on the Web. A centralized agent for information discovery has usually limited capabilities for finding diverse and distributed information online. The main thrust of the paper is to present a framework that allows distributed adaptive information KODAMA agents to work together to browse and retrieve distributed information based on the preexisting hyperlink structure on the Web and how this community of agents can automatically extract meta-information and cooperate to retrieve online distributed relevant information. We have developed the software architecture, and a working prototype showing the benefits to the Web of interactive architectures based on the coordination of the hyperlink structure on the network. The authors summarize the current results of the project, and discuss some ideas on future work.. |
| 207. | R. Fujimoto, A. Suganuma, T. Mine, Development of a Classroom Management System on the Web, Proc. of International Conference on Computers in Education, 55, 756-759, pp.756--759, 1999.11. |
| 208. | T. Mine, M. Higashi, M. Amamiya, Case Frame Acquisition and Verb Sense Disambiguation on a Large Scale Electronic Dictionary, Proc. of NLPRS(Natural Language Processing Pacific Rim Sympo.)'97 in Phuket, Thailand, pp.221-226, 1997.12. |
| 209. | H. Sato, T. Mine, T. Shoudai, H. Arimura, S. Hirokawa, On Web visualizing how programs run for teaching 2300 students, ICCE(International Conference on Computers in Education) 97 in Malaysia, pp.952--954, 1997.12. |
| 210. | T. Mine, K. Aso, M. Amamiya, Japanese Document Retrieval System on WWW using Dependency Relations between Words, Proc. of PACLING(Pacific Association for Computational LINGuistics)'97 in Ome, pp.209--215, 1997.09. |
| 211. | S. Hirokawa, T. Miyahara, T. Mine, T. Shoudai, M. Mori, H. Sato, A. Shinohara, M. Takeda, Teaching 2300 Students with WWW -- Practice and Experience at Kyushu University, Proc. of ERI'96, pp.59 -- 63, 1996.12. |
| 212. | Tsunenori Mine, Daisuke Matsuno, Akihiro Kogo, Makoto Amamiya, ACP2P : Agent Community based Peer-to-Peer Information Retrieval, the Third International Workshop on Agents and Peer-to-Peer Computing (AP2PC) (joint Workshop of AAMAS), Agents and Peer-to-Peer Computing 2004 LNCS Volume Editors Gianluca Moro, Sonia Bergamaschi and Karl Aberer to appear. |
| 213. | Makoto Amamiya, Haibo Yu, Tsunenori Mine, P2P Community Information Sharing Among Semantic MyPortals, the American Scientific Publishers, in press. |
| 214. | 峯 恒憲, Mixture-Preference Bayesian Matrix Factorization for implicit feedback datasets, The 35th ACM/SIGAPP Symposium On Applied Computing, 1427-1434. |
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