A practical algorithm to find the best subsequence patterns

Masahiro Hirao; Hiromasa Hoshino; Ayumi Shinohara; Masayuki Takeda; Setsuo Arikawa

doi:10.1016/S0304-3975(02)00182-2

A practical algorithm to find the best subsequence patterns

Masahiro Hirao, Hiromasa Hoshino, Ayumi Shinohara, Masayuki Takeda, Setsuo Arikawa

INF - System Information Sciences

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

Abstract

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. We regard it to find a subsequence pattern which separates these two sets. The problem is known to be NP-complete. We naturally generalize it to an optimization problem, where we try to find a subsequence pattern which maximally separates these two sets. We provide a practical algorithm to solve it exactly. Our algorithm uses two pruning heuristics based on the properties of subsequence languages, and utilizes the data structure called subsequence automata. We report some experimental results, which show these heuristics and the data structure contribute to reduce the search time.

Original language	English
Pages (from-to)	465-479
Number of pages	15
Journal	Theoretical Computer Science
Volume	292
Issue number	2
DOIs	https://doi.org/10.1016/S0304-3975(02)00182-2
Publication status	Published - 2003 Jan 27

Keywords

Optimal pattern discovery
Subsequence
Subsequence automata

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

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10.1016/S0304-3975(02)00182-2

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title = "A practical algorithm to find the best subsequence patterns",

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T1 - A practical algorithm to find the best subsequence patterns

AU - Hirao, Masahiro

AU - Hoshino, Hiromasa

AU - Shinohara, Ayumi

AU - Takeda, Masayuki

AU - Arikawa, Setsuo

PY - 2003/1/27

Y1 - 2003/1/27

N2 - 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. We regard it to find a subsequence pattern which separates these two sets. The problem is known to be NP-complete. We naturally generalize it to an optimization problem, where we try to find a subsequence pattern which maximally separates these two sets. We provide a practical algorithm to solve it exactly. Our algorithm uses two pruning heuristics based on the properties of subsequence languages, and utilizes the data structure called subsequence automata. We report some experimental results, which show these heuristics and the data structure contribute to reduce the search time.

AB - 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. We regard it to find a subsequence pattern which separates these two sets. The problem is known to be NP-complete. We naturally generalize it to an optimization problem, where we try to find a subsequence pattern which maximally separates these two sets. We provide a practical algorithm to solve it exactly. Our algorithm uses two pruning heuristics based on the properties of subsequence languages, and utilizes the data structure called subsequence automata. We report some experimental results, which show these heuristics and the data structure contribute to reduce the search time.

KW - Optimal pattern discovery

KW - Subsequence

KW - Subsequence automata

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