Hideo Bannai | Last modified date：2019.06.27 |

Associate Professor /
Mathematical Informatics

Department of Informatics

Faculty of Information Science and Electrical Engineering

Department of Informatics

Faculty of Information Science and Electrical Engineering

Graduate School

Undergraduate School

Homepage

##### https://str.i.kyushu-u.ac.jp/~bannai/

Academic Degree

PhD (Information Science and Technology)

Field of Specialization

Computer Science

Research

**Research Interests**

- Compressed String Mining

keyword : compressed string processing, data mining

2010.04. - Optimal pattern discovery from string data

keyword : pattern discovery, string algorithms

2002.01.

**Academic Activities**

**Papers**

1. | Hideo Bannai, I. Tomohiro, Shunsuke Inenaga, Yuto Nakashima, Masayuki Takeda, Kazuya Tsuruta, The "runs" theorem, SIAM Journal on Computing, 10.1137/15M1011032, 46, 5, 1501-1514, 2017.09, We give a new characterization of maximal repetitions (or runs) in strings based on Lyndon words. The characterization leads to a proof of what was known as the "runs" conjecture [R. M. Kolpakov andG.Kucherov, Proceedings of the IEEE Symposium on Foundations of Computer Science (FOCS), IEEE Computer Society, Los Alamitos, CA, 1999, pp. 596-604]), which states that the maximum number of runs ρ(n) in a string of length n is less than n. The proof is remarkably simple, considering the numerous endeavors to tackle this problem in the last 15 years, and significantly improves our understanding of how runs can occur in strings. In addition, we obtain an upper bound of 3n for the maximum sum of exponents σ(n) of runs in a string of length n, improving on the best known bound of 4.1n by Crochemore et al. [J. Discrete Algorithms, 14 (2012), pp. 29-36], as well as other improved bounds on related problems. The characterization also gives rise to a new, conceptually simple linear-time algorithm for computing all the runs in a string. A notable characteristic of our algorithm is that, unlike all existing linear-time algorithms, it does not utilize the Lempel-Ziv factorization of the string. We also establish a relationship between runs and nodes of the Lyndon tree, which gives a simple optimal solution to the 2-period query problem that was recently solved by Kociumaka et al. [Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, (SODA) 2015, San Diego, CA, SIAM, Philadelphia, 2015, pp. 532-551].. |

2. | Yuto Nakashima, Takashi Okabe, Tomohiro I, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Inferring strings from Lyndon factorization, Theoretical Computer Science, 10.1016/j.tcs.2017.05.038, 2017.08, The Lyndon factorization of a string w is a unique factorization ℓ1p1,...,ℓmpm of w such that ℓ1,...,ℓm is a sequence of Lyndon words that is monotonically decreasing in lexicographic order. In this paper, we consider the reverse-engineering problem on Lyndon factorization: Given a sequence S=((s1,p1),...,(sm,pm)) of ordered pairs of positive integers, find a string w whose Lyndon factorization corresponds to the input sequence S, i.e., the Lyndon factorization of w is in a form of ℓ1p1,...,ℓmpm with |ℓi|=si for all 1≤i≤m. Firstly, we show that there exists a simple O(n)-time algorithm if the size of the alphabet is unbounded, where n is the length of the output string. Secondly, we present an O(n)-time algorithm to compute a string over an alphabet of the smallest size. Thirdly, we show how to compute only the size of the smallest alphabet in O(m) time. Fourthly, we give an O(m)-time algorithm to compute an O(m)-size representation of a string over an alphabet of the smallest size. Finally, we propose an efficient algorithm to enumerate all strings whose Lyndon factorizations correspond to S.. |

3. | Yohei Ueki, Diptarama, Masatoshi Kurihara, Yoshiaki Matsuoka, Kazuyuki Narisawa, Ryo Yoshinaka, Hideo Bannai, Shunsuke Inenaga, Ayumi Shinohara, Longest Common Subsequence in at Least k Length Order-Isomorphic Substrings, Proceedings of the 43rd International Conference on Current Trends in Theory and Practice of Computer Science, 10.1007/978-3-319-51963-0_28, 363-374, 2017.01. |

4. | Yoshiaki Matsuoka, Takahiro Aoki, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Generalized pattern matching and periodicity under substring consistent equivalence relations, THEORETICAL COMPUTER SCIENCE, 10.1016/j.tcs.2016.02.017, 656, 225-233, 2016.12. |

5. | Tomohiro I, Yuto Nakashima, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Faster Lyndon factorization algorithms for SLP and LZ78 compressed text, THEORETICAL COMPUTER SCIENCE, 10.1016/j.tcs.2016.03.005, 656, 215-224, 2016.12. |

6. | Golnaz Badkobeh, Hideo Bannai, Keisuke Goto, Tomohiro I, Costas S. Iliopoulos, Shunsuke Inenaga, Simon J. Puglisi, Shiho Sugimoto, Closed factorization, DISCRETE APPLIED MATHEMATICS, 10.1016/j.dam.2016.04.009, 212, 23-29, 2016.10. |

7. | Takaaki Nishimoto, Tomohiro I, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Dynamic Index and LZ Factorization in Compressed Space, Proceedings of The Prague Stringology Conference 2016 (PSC 2016), 158-171, 2016.08, [URL]. |

8. | Hiroe Inoue, Yoshiaki Matsuoka, Yuto Nakashima, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Computing Smallest and Largest Repetition Factorizations in O(n log n) Time, Proceedings of The Prague Stringology Conference 2016 (PSC 2016), 135-145, 2016.08, [URL]. |

9. | Takaaki Nishimoto, Tomohiro I, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Fully Dynamic Data Structure for LCE Queries in Compressed Space, Proceedings of 41st International Symposium on Mathematical Foundations of Computer Science (MFCS 2016), 10.4230/LIPIcs.MFCS.2016.72, 72:1-72:15, 2016.08, [URL]. |

10. | Takuya Mieno, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Shortest Unique Substring Queries on Run-Length Encoded Strings, Proceedings of 41st International Symposium on Mathematical Foundations of Computer Science (MFCS 2016), 10.4230/LIPIcs.MFCS.2016.69, 69:1-69:11, 2016.08, [URL]. |

11. | Yuta Fujishige, Yuki Tsujimaru, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Computing DAWGs and Minimal Absent Words in Linear Time for Integer Alphabets, Proceedings of 41st International Symposium on Mathematical Foundations of Computer Science (MFCS 2016), 10.4230/LIPIcs.MFCS.2016.38, 38:1-38:14, 2016.08, [URL]. |

12. | Yuta Fujishige, Michitaro Nakamura, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Finding Gapped Palindromes Online, Proceedings of the 27th International Workshop on Combinatorial Algorithms (IWOCA 2016), 10.1007/978-3-319-44543-4_15, 2016.08. |

13. | Yoshiaki Matsuoka, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Factorizing a String into Squares in Linear Time, 27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016), 10.4230/LIPIcs.CPM.2016.27, 27:1-27:12, 2016.06, [URL]. |

14. | Yuka Tanimura, Tomohiro I, Shunsuke Inenaga, Hideo Bannai, Simon J. Puglisi, Masayuki Takeda, Deterministic Sub-Linear Space LCE Data Structures With Efficient Construction, 27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016), 10.4230/LIPIcs.CPM.2016.1, 1:1-1:10, 2016.06, [URL]. |

15. | Makoto Nishida, Tomohiro I, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Inferring Strings from Full Abelian Periods, Proceedings of the 26th International Symposium on Algorithms and Computation (ISAAC 2015), 10.1007/978-3-662-48971-0_64, 768-779, 2015.12. |

16. | Yuka Tanimura, Yuta Fujishige, Tomohiro I, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, A Faster Algorithm for Computing Maximal alpha-gapped Repeats in a String, Proceedings of the 22nd International Symposium on String Processing and Information Retrieval (SPIRE 2015), 10.1007/978-3-319-23826-5_13, 124-136, 2015.09. |

17. | Hideo Bannai, Shunsuke Inenaga, Tomasz Kociumaka, Arnaud Lefebvre, Jakub Radoszewski, Wojciech Rytter, Shiho Sugimoto, Tomasz Walen, Efficient Algorithms for Longest Closed Factor Array, Proceedings of the 22nd International Symposium on String Processing and Information Retrieval (SPIRE 2015), 10.1007/978-3-319-23826-5_10, 95-102, 2015.09. |

18. | Yuto Nakashima, Tomohiro I, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Constructing LZ78 tries and position heaps in linear time for large alphabets, INFORMATION PROCESSING LETTERS, 10.1016/j.ipl.2015.04.002, 115, 9, 655-659, 2015.09. |

19. | Takaaki Nishimoto, Yuto Nakashima, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Computing Left-Right Maximal Generic Words, Proceedings of The Prague Stringology Conference 2015 (PSC 2015), 5-16, 2015.08. |

20. | Hideo Bannai, Travis Gagie, Shunsuke Inenaga, Juha Kärkkäinen, Dominik Kempa, Marcin Piatkowski, Simon J. Puglisi, Shiho Sugimoto, Diverse Palindromic Factorization Is NP-complete, Proceedings of the 19th International Conference on Developments in Language Theory (DLT 2015), 10.1007/978-3-319-21500-6_6, 85-96, 2015.07. |

21. | Keisuke Goto, Hideo Bannai, Shunsuke Inenaga, Masayuki Takeda, LZD Factorization: Simple and Practical Online Grammar Compression with Variable-to-Fixed Encoding, Proceedings of the 26th Annual Symposium on Combinatorial Pattern Matching (CPM 2015), 10.1007/978-3-319-19929-0_19, 219-230, 2015.06. |

22. | Yoshiaki Matsuoka, Tomohiro I, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Semi-dynamic compact index for short patterns and succinct van Emde Boas tree, Proceedings of the 26th Annual Symposium on Combinatorial Pattern Matching (CPM 2015), 10.1007/978-3-319-18173-8_29, 355-366, 2015.06. |

23. | Yuya Tamakoshi, Keisuke Goto, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, An opportunistic text indexing structure based on run length encoding, Proceedings of the 9th International Conference on Algorithms and Complexity (CIAC 2015), 10.1007/978-3-319-18173-8_29, 390-402, 2015.05. |

24. | Tomohiro I, Takaaki Nishimoto, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Compressed automata for dictionary matching, THEORETICAL COMPUTER SCIENCE, 10.1016/j.tcs.2015.01.019, 578, 30-41, 2015.05. |

25. | Tomohiro I, Wataru Matsubara, Kouji Shimohira, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Kazuyuki Narisawa, Ayumi Shinohara, Detecting regularities on grammar-compressed strings, INFORMATION AND COMPUTATION, 10.1016/j.ic.2014.09.009, 240, 74-89, 2015.02. |

26. | Hideo Bannai, Tomohiro I, Shunsuke Inenaga, Yuto Nakashima, Masayuki Takeda, Kazuya Tsuruta, A new characterization of maximal repetitions by Lyndon trees, Proceedings of the 26th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA '15), 10.1137/1.9781611973730.38, 562-571, 2015.01, We give a new characterization of maximal repetitions (or runs) in strings, using a tree defined on recursive standard factorizations of Lyndon words, called the Lyndon tree. The characterization leads to a remarkably simple novel proof of the linearity of the maximum number of runs $ho(n)$ in a string of length $n$. Furthermore, we show an upper bound of $ ho(n) < 1.5n$, which improves on the best upper bound $1.6n$ (Crochemore & Ilie 2008) that does not rely on computational verification. The proof also gives rise to a new, conceptually simple linear-time algorithm for computing all the runs in a string. A notable characteristic of our algorithm is that, unlike all existing linear-time algorithms, it does {em not} utilize the Lempel-Ziv factorization of the string.. |

27. | Shohei Matsuda, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Computing Abelian Covers and Abelian Runs, Proceedings of The Prague Stringology Conference 2014 (PSC 2014), 43-51, 2014.09, Two strings u and v are said to be Abelian equivalent if u is a permutation of the characters of v. We introduce two new regularities on strings w.r.t. Abelian equivalence, called Abelian covers and Abelian runs, which are generalizations of covers and runs of strings, respectively. We show how to determine in O(n) time whether or not a given string w of length n has an Abelian cover. Also, we show how to compute an O(n^2)-size representation of (possibly exponentially many) Abelian covers of w in O(n^2) time. Moreover, we present how to compute all Abelian runs in w in O(n^2) time, and state that the maximum number of all Abelian runs in a string of length n is Omega(n^2).. |

28. | Yuto Nakashima, Takashi Okabe, Tomohiro I, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Inferring Strings from Lyndon factorization, Proceedings of the 39th International Symposium on Mathematical Foundations of Computer Science (MFCS 2014), 10.1007/978-3-662-44465-8_48, 565-576, 2014.08, The Lyndon factorization of a string $w$ is a unique factorization $ell_1^{p_1}, ldots, ell_m^{p_m}$ of $w$ s.t. $ell_1, dots, ell_m$ is a sequence of Lyndon words that is monotonically decreasing in lexicographic order. In this paper, we consider the emph{reverse-engineering problem on Lyndon factorization}: Given a sequence $S = ((s_1, p_1), ldots, (s_m, p_m))$ of ordered pairs of positive integers, find a string $w$ whose Lyndon factorization corresponds to the input sequence $S$, i.e., the Lyndon factorization of $w$ is in a form of $ell_1^{p_1}, ldots, ell_m^{p_m}$ with $|ell_i| = s_i$ for all $1 leq i leq m$. Firstly, we show that there exists a simple $O(n)$-time algorithm if the size of the alphabet is unbounded, where $n$ is the length of the output string. Secondly, we present an $O(n)$-time algorithm to compute a string over an alphabet of the smallest size. Thirdly, we show how to compute only the size of the smallest alphabet in $O(m)$ time. Fourthly, we give an $O(m)$-time algorithm to compute an $O(m)$-size representation of a string over an alphabet of the smallest size. Finally, we propose an efficient algorithm to enumerate all strings whose Lyndon factorizations correspond to $S$.. |

29. | Tomohiro I, Shiho Sugimoto, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Computing Palindromic Factorizations and Palindromic Covers On-line, Proceedings of the 25th Annual Symposium on Combinatorial Pattern Matching (CPM 2014), 10.1007/978-3-319-07566-2_16, 150-161, 2014.06, A palindromic factorization of a string w is a factorization of w consisting only of palindromic substrings of w. In this paper, we present an on-line O(n logn)-time O(n)-space algorithm to compute smallest palindromic factorizations of all prefixes of w, where n is the length of a given string w. We then show how to extend this algorithm to compute smallest maximal palindromic factorizations of all prefixes of w, consisting only of maximal palindromes (non-extensible palindromic substring) of each prefix, in O(n logn) time and O(n) space, in an on-line manner. We also present an on-line O(n)-time O(n)-space algorithm to compute a smallest palindromic cover of w.. |

30. | Jun'ichi Yamamoto, Tomohiro I, Hideo Bannai, Shunsuke Inenaga, Masayuki Takeda, Faster Compact On-Line Lempel-Ziv Factorization, Proceedings of the 31st Symposium on Theoretical Aspects of Computer Science (STACS 2014), 10.4230/LIPIcs.STACS.2014.675, 675-678, 2014.03. |

31. | Keisuke Goto and Hideo Bannai, Space Efficient Linear Time Lempel-Ziv Factorization for Small Alphabets, Data Compression Conference 2014 (DCC 2014), 10.1109/DCC.2014.62, 163-172, 2014.03. |

32. | Eiichi Bannai, Etsuko Bannai, Hideo Bannai, On the existence of tight relative 2-designs on binary Hamming association schemes, Discrete Mathematics, 10.1016/j.disc.2013.09.013, 314, 6, 17-37, 2014.01, [URL]. |

33. | Tomohiro I, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Inferring strings from suffix trees and links on a binary alphabet, Discrete Applied Mathematics, 10.1016/j.dam.2013.02.033, 163(3):316-325, 2014.01, [URL], A suffix tree, which provides us with a linear space full-text index of a given string, is a fundamental data structure for string processing and information retrieval. In this paper we consider the reverse engineering problem on suffix trees: given an unlabeled ordered rooted tree T accompanied with a node-to-node transition function f, infer a string whose suffix tree and its suffix links for inner nodes are isomorphic to T and f, respectively. Also, we consider the enumeration problem in which we enumerate all strings corresponding to an input tree and links. By introducing new characterizations of suffix trees, we show that the reverse engineering problem and the enumeration problem on suffix trees on a binary alphabet can be solved in optimal time.. |

34. | Kazuya Tsuruta, Shunsuke Inenaga, Hideo Bannai, and Masayuki Takeda, Shortest Unique Substrings Queries in Optimal Time, Proceedings of the 40th International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM 2014), 10.1007/978-3-319-04298-5_44, Lecture Notes in Computer Science 8327:503-513, 2014.01. |

35. | Tomohiro I, Yuto Nakashima, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Faster Lyndon factorization algorithms for SLP and LZ78 compressed text, Proceedings of the 20th International Symposium on String Processing and Information Retrieval (SPIRE 2013), 10.1007/978-3-319-02432-5_21, Lecture Notes in Computer Science 8214:174-185, 2013.10. |

36. | Tomohiro I, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Computing Reversed Lempel-Ziv Factorization Online, Proceedings of The Prague Stringology Conference 2013 (PSC 2013), 107-118, 2013.09. |

37. | Tomohiro I, Hideo Bannai, Shunsuke Inenaga, Masayuki Takeda, Kazuyuki Narisawa, Ayumi Shinohara, Detecting Regularities on Grammar-compressed Strings, Proceedings of the 38th International Symposium on Mathematical Foundations of Computer Science (MFCS 2013), 10.1007/978-3-642-40313-2_51, Lecture Notes in Computer Science 8087, 571-582, Lecture Notes in Computer Science 8087:571-582, 2013.08. |

38. | Tomohiro I, Takaaki Nishimoto, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Compressed Automata for Dictionary Matching, Proceedings of the 18th International Conference on Implementation and Application of Automata (CIAA 2013),, 2013.07. |

39. | Hideo Bannai, Pawel Gawrychowski, Shunsuke Inenaga and Masayuki Takeda, Converting SLP to LZ78 in almost linear time, Proceedings of the 24th Annual Symposium on Combinatorial Pattern Matching (CPM 2013), 2013.06. |

40. | Tomohiro I, Yuto Nakashima, Shunsuke Inenaga, Hideo Bannai, Masayuki Takeda, Efficient Lyndon factorization of grammar compressed text, Proceedings of the 24th Annual Symposium on Combinatorial Pattern Matching (CPM 2013), 2013.06. |

41. | Toshiya Tanaka, Tomohiro I, Shunsuke Inenaga, Hideo Bannai, and Masayuki Takeda, Computing convolution on grammar-compressed text, Data Compression Conference 2013 (DCC 2013), 451-460, 2013.03. |

42. | Yuya Tamakoshi, Tomohiro I, Shunsuke Inenaga, Hideo Bannai, and Masayuki Takeda, From Run Length Encoding to LZ78 and Back Again, Data Compression Conference 2013 (DCC 2013), 143-152, 2013.03. |

43. | Keisuke Goto and Hideo Bannai, Simpler and Faster Lempel Ziv Factorization, Data Compression Conference 2013 (DCC 2013), 133-142, 2013.03. |

44. | Takashi Katsura, Kazuyuki Narisawa, Ayumi Shinohara, Hideo Bannai and Shunsuke Inenaga, Permuted pattern matching on multi-track strings, Proceedings of the 38th International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM 2013), 10.1007/978-3-642-35843-2_25, Lecture Notes in Computer Science 7741:280-291, 2013.01, [URL]. |

45. | Keisuke Goto, Hideo Bannai, Shunsuke Inenaga, Masayuki Takeda, Fast q-gram mining on SLP compressed strings, Journal of Discrete Algorithms, http://dx.doi.org/10.1016/j.jda.2012.07.006, 18, 89-99, 2013.01, [URL], We present simple and efficient algorithms for calculating q-gram frequencies on strings represented in compressed form, namely, as a straight line program (SLP). Given an SLP of size n that represents string T, we present an O(qn) time and space algorithm that computes the occurrence frequencies of all q-grams in T. Computational experiments show that our algorithm and its variation are practical for small q, actually running faster on various real string data, compared to algorithms that work on the uncompressed text. We also discuss applications in data mining and classification of string data, for which our algorithms can be useful.. |

46. | Yuto Nakashima, Tomohiro I, Shunsuke Inenaga, Hideo Bannai, and Masayuki Takeda, The position heap of a trie, Proceedings of the 19th International Symposium on String Processing and Information Retrieval (SPIRE 2012), 10.1007/978-3-642-34109-0_38, Lecture Notes in Computer Science 7608:360-371, 2012.10, [URL]. |

47. | Hideo Bannai, Shunsuke Inenaga, and Masayuki Takeda, Efficient LZ78 factorization of grammar compressed text, Proceedings of the 19th International Symposium on String Processing and Information Retrieval (SPIRE 2012), 10.1007/978-3-642-34109-0_10, 2012.10, [URL]. |

48. | Hideo Bannai, Travis Gagie, Tomohiro I, Shunsuke Inenaga, Gad M. Landau, Moshe Lewenstein, An Efficient Algorithm to Test Square-Freeness of Strings Compressed by Straight-Line Programs, Information Processing Letters, 10.1016/j.ipl.2012.06.017, 112, 19, 711-714, 2012.10, [URL]. |

49. | Tomohiro I, Yuki Enokuma, Hideo Bannai, and Masayuki Takeda, General Algorithms for Mining Closed Flexible Patterns under Various Equivalence Relations, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2012), 10.1007/978-3-642-33486-3_28, Lecture Notes in Computer Science 7524:435-450, 2012.09, [URL]. |

50. | Keisuke Goto, Hideo Bannai, Shunsuke Inenaga, Masayuki Takeda, Speeding up q-gram mining on grammar-based compressed texts, Proceedings of the 23rd Annual Symposium on Combinatorial Pattern Matching (CPM 2012), 10.1007/978-3-642-31265-6_18, Lecture Notes in Computer Science 7354:220-231, 2012.07, [URL]. |

51. | Shunsuke Inenaga, Hideo Bannai, Finding Characteristic Substrings from Compressed Texts, International Journal of Foundations of Computer Science, 10.1142/S0129054112400126, 23, 2, 261-280, 2012.02, [URL]. |

52. | Keisuke Goto, Hideo Bannai, Shunsuke Inenaga, Masayuki Takeda, Computing q-gram Non-overlapping Frequencies on SLP Compressed Texts, Proceedings of the 38th International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM 2012), 10.1007/978-3-642-27660-6_25, Lecture Notes in Computer Science 7147:301-312, 2012.01. |

53. | Keisuke Goto, Hideo Bannai, Shunsuke Inenaga, Masayuki Takeda, Fast q-gram Mining on SLP Compressed Strings, Proceedings of the 18th International Symposium on String Processing and Information Retrieval (SPIRE 2011), 10.1007/978-3-642-24583-1_27, Lecture Notes in Computer Science 7024:135-146, 2011.10. |

54. | Takanori Yamamoto, Hideo Bannai, Shunsuke Inenaga, Masayuki Takeda, Faster Subsequence and Don't-Care Pattern Matching on Compressed Texts, Proceedings of the 22nd Annual Symposium on Combinatorial Pattern Matching (CPM 2011), 10.1007/978-3-642-21458-5_27, Lecture Notes in Computer Science 6661:309-322, 2011.06. |

55. | Ryosuke Nakamura, Shunsuke Inenaga, Hideo Bannai, Takashi Funamoto, Masayuki Takeda, and Ayumi Shinohara, Linear-Time Text Compression by Longest-First Substitution, Algorithms, 10.3390/a2041429, 2, 4, 1429-1448, 2009.11, [URL]. |

56. | Takanori Yamamoto, Hideo Bannai, Masao Nagasaki, and Satoru Miyano, Better Decomposition Heuristics for the Maximum-Weight Connected Graph Problem using Betweenness Centrality, Proceedings of the 12th International Conference on Discovery Science (DS2009), Lecture Notes in Computer Science 5808:465-472, 2009.10, [URL]. |

57. | Kazunori Hirashima, Hideo Bannai, Wataru Matsubara, Akira Ishino and Ayumi Shinohara, Bit-parallel algorithms for computing all the runs in a string, Proceedings of The Prague Stringology Conference 2009 (PSC 2009), 203-213, 2009.09, [URL]. |

58. | Shunsuke Inenaga and Hideo Bannai, Finding Characteristic Substrings from Compressed Texts, Proceedings of The Prague Stringology Conference 2009 (PSC 2009), 40–54, 2009.09, [URL]. |

59. | Tomohiro I, Satoshi Deguchi, Hideo Bannai, Shunsuke Inenaga, and Masayuki Takeda, Lightweight Parameterized Suffix Array Construction, Proceedings of the 20th International Workshop on Combinatorial Algorithms (IWOCA 2009), 2009.06. |

60. | Satoshi Deguchi, Fumihito Higashijima, Hideo Bannai, Shunsuke Inenaga, and Masayuki Takeda, Parameterized Suffix Arrays for Binary Strings, Proceedings of The Prague Stringology Conference 2008 (PSC2008), 84-94, 2008.09, [URL]. |

61. | Kazuhiko Kusano, Wataru Matsubara, Akira Ishino, Hideo Bannai and Ayumi Shinohara, New Lower Bounds for the Maximum Number of Runs in a String, Proceedings of The Prague Stringology Conference 2008 (PSC2008), 140-145, 2008.09, [URL]. |

62. | Hideo Bannai, Kohei Hatano, Shunsuke Inenaga, Masayuki Takeda, Practical Algorithms for Pattern Based Linear Regression, Proceedings of the 8th International Conference on Discovery Science, 3735, 44-56, Lecture Notes in Artificial Intelligence 3735:44-56, 2005.10. |

63. | Hideo Bannai, Heikki Hyyro, Ayumi Shinohara, Masayuki Takeda, Kenta Nakai, and Satoru Miyano, An O(N^2) Algorithm for Discovering Optimal Boolean Pattern Pairs, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10.1109/TCBB.2004.36, 1, 4, 159-170, 1(4): 159-170, 2004.12. |

64. | Hideo Bannai, Shunsuke Inenaga, Ayumi Shinohara, Masayuki Takeda, and Satoru Miyano, Efficiently Finding Regulatory Elements using Correlation with Gene Expression, Journal of Bioinformatics and Computational Biology, 2(2):273-288, 2004.01. |

65. | Hideo Bannai, Shunsuke Inenaga, Ayumi Shinohara, and Masayuki Takeda, Inferring Strings from Graphs and Arrays, Proceedings of the 28th International Symposium on Mathematical Foundations of Computer Science, 2747, 208-217, Lecture Notes in Computer Science 2747:208-217, 2003.01. |

66. | Hideo Bannai, Shunsuke Inenaga, Ayumi Shinohara, Masayuki Takeda, and Satoru Miyano, A String Pattern Regression Algorithm and Its Application to Pattern Discovery in Long Introns, Genome Informatics, 13:3-11, 2002.12. |

67. | Hideo Bannai, Yoshinori Tamada, Osamu Maruyama, Kenta Nakai, and Satoru Miyano, Extensive Feature Detection of N-Terminal Protein Sorting Signals, Bioinformatics, 10.1093/bioinformatics/18.2.298, 18, 2, 298-305, 18(2):298-305, 2002.01. |

**Works, Software and Database**

1. | [URL]. |

2. | [URL]. |

3. | [URL]. |

4. | programs for finding and counting runs (maximal repetitions) in a string [URL]. |

5. | iPSORT is a subcellular localization site predictor for N-terminal sorting signals. Given a protein sequence , it will predict whether it contains a Signal Peptide (SP), Mitochondrial Targeting Peptide (mTP), or Chloroplast Transit Peptide (cTP). http://hc.ims.u-tokyo.ac.jp/iPSORT/. |

**Presentations**

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