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- Shuichi Mitarai, Masahiro Hirao, Tetsuya Matsumoto, Ayumi Shinohara, Masayuki Takeda, Setsuo Arikawa
- Data Compression Conference
- 2001

Sequitur due to Nevill-Manning and Witten. [18] is a powerful program to infer a phrase hierarchy from the input text, that also provides extremely effective compression of large quantities of semi-structured text [17]. In this paper, we address the problem of searching in Sequitur compressed text directly. We show a compressed pattern matching algorithm… (More)

- Masahiro Hirao, Hiromasa Hoshino, Ayumi Shinohara, Masayuki Takeda, Setsuo Arikawa
- Discovery Science
- 2000

Given two sets of strings, consider the problem to find a subsequence that is common to one set but never appears in the other set. The problem is known to be NP-complete. We generalize the problem to an optimization problem, and give a practical algorithm to solve it exactly. Our algorithm uses pruning heuristic and subsequence automata, and can find the… (More)

- Masahiro Hirao, Shunsuke Inenaga, Ayumi Shinohara, Masayuki Takeda, Setsuo Arikawa
- Discovery Science
- 2001

Episode pattern is a generalized concept of subsequence pattern where the length of substring containing the subsequence is bounded. Given two sets of strings, consider an optimization problem to find a best episode pattern that is common to one set but not common in the other set. The problem is known to be NP-hard. We give a practical algorithm to solve… (More)

- Ayumi Shinohara, Masayuki Takeda, Setsuo Arikawa, Masahiro Hirao, Hiromasa Hoshino, Shunsuke Inenaga
- Progress in Discovery Science
- 2002

Finding a pattern which separates two sets is a critical task in discovery. Given two sets of strings, consider the problem to find a subsequence that is common to one set but never appears in the other set. The problem is known to be NP-complete. Episode pattern is a generalized concept of subsequence pattern where the length of substring containing the… (More)

- Masahiro Hirao, Ayumi Shinohara, Masayuki Takeda, Setsuo Arikawa
- SPIRE
- 2000

We consider a fully compressed pattern matching problem, where both text T and pattern P are given by its succinct representation, in terms of straight-line programs and its variant. The length of the text T and pattern P may grow exponentially with respect to its description size n and m, respectively. The best known algorithm for the problem runs in O(nm)… (More)

We address the problem of musical sequence comparison for melodic similarity. Starting with a very simple similarity measure, we improve it step-by-step to finally obtain an acceptable measure. While the measure is still simple and has only two tuning parameters, it is better than that proposed by Mongeau and Sankoff (1990) in the sense that it can… (More)

Given two sets of strings, consider the problem to find a subsequence that is common to one set but never appears in the other set. The problem is known to be NP-complete. We generalize the problem to an optimization problem, and give a practical algorithm to solve it exactly. Our algorithm uses pruning heuristic and subsequence automata, and can find the… (More)

- Masahiro Hirao, Toshiaki Aida
- 2015 15th International Conference on Control…
- 2015

We approach to the problem of inverse halftoning within the frameworks of Bayesian inference and compressed sensing, which is one of the most effective signal processing methods through sparse representation. In this paper, we adopt the K-SVD dictionary for the sparse representation of an original image to be inferred, and develop our previous work with the… (More)

- Kosuke Okuda, E Sasai, Haruki Nagata, Keisuke Hayakawa, Masahiro Hirao
- Kurinikaru sutadī = Clinical study
- 1986

We show an efficient pattern-matching algorithm for strings that are succinctly described in terms of straight-line programs, in which the constants are symbols and the only operation is the concatenation. In this paper, both text T and pattern P are given by straight-line programs T and P. The length of the text T (pattern P , resp.) may grow exponentially… (More)

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