Kyushu University Academic Staff Educational and Research Activities Database
List of Papers
Shimizu Toshiyuki Last modified dateļ¼š2024.06.03

Associate Professor / Library

1. Hideaki Ohashi, Toshiyuki Shimizu, Masatoshi Yoshikawa, Does Student-Submission Allocation Affect Peer Assessment Accuracy?, IEICE Transactions on Information and Systems, 10.1587/transinf.2021DAP0002, E105D, 5, 888-897, 2022.05, Peer assessment in education has pedagogical benefits and is a promising method for grading a large number of submissions. At the same time, student reliability has been regarded as a problem; consequently, various methods of estimating highly reliable grades from scores given by multiple students have been proposed. Under most of the existing methods, a nonadaptive allocation pattern, which performs allocation in advance, is assumed. In this study, we analyze the effect of student-submission allocation on score estimation in peer assessment under a nonadaptive allocation setting. We examine three types of nonadaptive allocation methods, random allocation, circular allocation and group allocation, which are considered the commonly used approaches among the existing nonadaptive peer assessment methods. Through simulation experiments, we show that circular allocation and group allocation tend to yield lower accuracy than random allocation. Then, we utilize this result to improve the existing adaptive allocation method, which performs allocation and assessment in parallel and tends to make similar allocation result to circular allocation. We propose the method to replace part of the allocation with random allocation, and show that the method is effective through experiments..
2. Hideaki Ohashi, Toshiyuki Shimizu, Masatoshi Yoshikawa, Flexible and Fast Similarity Search for Enriched Trajectories, IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 10.1587/transinf.2016EDP7482, E100D, 9, 2081-2091, 2017.09, In this study, we focus on a method to search for similar trajectories. In the majority of previous works on searching for similar trajectories, only raw trajectory data were used. However, to obtain deeper in-sights, additional time-dependent trajectory features should be utilized depending on the search intent. For instance, to identify similar combination plays in soccer games, such additional features include the movements of the team players. In this paper, we develop a framework to flexibly search for similar trajectories associated with time-dependent features, which we call enriched trajectories. In this framework, weights, which represent the relative importance of each feature, can be flexibly given by users. Moreover, to facilitate fast searching, we first propose a lower bounding measure of the DTW distance between enriched trajectories, and then we propose algorithms based on this lower bounding measure. We evaluate the effectiveness of the lower bounding measure and compare the performances of the algorithms under various conditions using soccer data and synthetic data. Our experimental results suggest that the proposed lower bounding measure is superior to the existing measure, and one of the proposed algorithms, which is based on the threshold algorithm, is suitable for practical use..
3. Akira Takahashi, Masashi Tatedoko, Toshiyuki Shimizu, Hiroko Kinutani, Masatoshi Yoshikawa, Metadata management for integration and analysis of earth observation data, Journal of Software, 10.4304/jsw.5.2.168-178, 5, 2, 168-178, 2010.02, Earth observation technologies have developed rapidly during the past few decades. Substantial amounts of earth observation data have been acquired and are currently stored in the literature and databases for various research fields such as climatology, oceanography, agriculture, and ecology. Analyzing and integrating such data might produce valuable data products to promote better understanding of the global environment and to help solve global environmental issues. However, most institutions store and manage their earth observation data independently, with little metadata. Scientists have to struggle to search for valuable data from information outside their research domains and seek uses for these. This paper introduces a conceptual model of earth observation data. Utilizing a model to express earth observation items associated with ontologies, the model is a simple quintuple with information extracted from conventional data models, and it is used to uniquely determine portions of earth observation data, which enables flexible annotations to these data. We also introduce our systems to manage the metadata and user interfaces to encourage users to add annotations to earth observation data that can help scientists discover and understand useful information that can support their research. © 2010 Academy Publisher..
4. Umaporn Supasitthimethee, Toshiyuki Shimizu, Masatoshi Yoshikawa, Kriengkrai Porkaew, XSemantic: An Extension of LCA Based XML Semantic Search, IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 10.1587/transinf.E92.D.1079, E92D, 5, 1079-1092, 2009.05, One of the most convenient ways to query XML data is a keyword search because it does not require any knowledge of XML structure or learning a new user interface. However, the keyword search is ambiguous. The users may use different terms to search for the same information. Furthermore, it is difficult for a system to decide which node is likely to be chosen as a return node and how much information should be included in the result. To address these challenges, we propose an XML semantic search based on keywords called XSemantic. On the one hand, we give three definitions to complete in terms of semantics. Firstly, the semantic term expansion, our system is robust from the ambiguous keywords by using the domain ontology. Secondly, to return semantic meaningful answers,, we automatically infer the return information from the user queries and take advantage of the shortest path to return meaningful connections between keywords. Thirdly, we present the semantic ranking that reflects the degree of similarity as well as the semantic relationship so that the search results with the higher relevance are presented to the users first. On the other hand, in the LCA and the proximity search approaches, we investigated the problem of information included in the search results. Therefore, we introduce the notion of the Lowest Common Element Ancestor (LCEA) and define our simple rule without any requirement on the schema information such as the DTD or XML Schema. The first experiment indicated that XSemantic not only properly infers the return information but also generates compact meaningful results. Additionally, the benefits of our proposed semantics are demonstrated by the second experiment..
5. T Shimizu, M Yoshikawa, Full-text and structural indexing of XML documents on B+-tree, IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 10.1093/ietisy/e89-d.1.237, E89D, 1, 237-247, 2006.01, XML query processing is one of the most active areas of database research. Although the main focus of past research has been the processing of structural XML queries, there are growing demands for a full-text search for XML documents. In this paper, we propose XICS (XML Indices for Content and Structural search), which aims at high-speed processing of both full-text and structural queries in XML documents. An important design principle of our indices is the use of a B+-tree. To represent the structural information of XML trees, each node in the XML tree is labeled with an identifier. The identifier contains an integer number representing the path information from the root node. XICS consist of two types of indices, the COB-tree (COntent B+-tree) and the STB-tree (STructure B+-tree). The search keys of the COB-tree are a pair of text fragments in the XML document and the identifiers of the leaf nodes that contain the text, whereas the search keys of the STB-tree are the node identifiers. By using a node identifier in the search keys, we can retrieve only the entries that match the path information in the query. The STB-tree can filter nodes using structural conditions in queries, while the COB-tree can filter nodes using text conditions. We have implemented a COB-tree and an STB-tree using GiST and examined index size and query processing time. Our experimental results show the efficiency of XICS in query processing..