抄録
The classificatory power of a pattern is measured by how well it separates two given sets of strings. This paper gives practical algorithms to find the fixed/variable-length-don't-care pattern (FVLDC pattern) and approximate FVLDC pattern which are most classificatory for two given string sets. We also present algorithms to discover the best window-accumulated FVLDC pattern and window-accumulated approximate FVLDC pattern. All of our new algorithms run in practical amount of time by means of suitable pruning heuristics and fast pattern matching techniques.
| 元の言語 | 英語 |
|---|---|
| ページ（範囲） | 486-493 |
| ページ数 | 8 |
| ジャーナル | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| 巻 | 2843 |
| 出版物ステータス | 出版済み - 12 1 2003 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
これを引用
Discovering most classificatory patterns for very expressive pattern classes. / Takeda, Masayuki; Inenaga, Shunsuke; Bannai, Hideo; Shinohara, Ayumi; Arikawa, Setsuo.
：: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 巻 2843, 01.12.2003, p. 486-493.研究成果: ジャーナルへの寄稿 › 記事
}
TY - JOUR
T1 - Discovering most classificatory patterns for very expressive pattern classes
AU - Takeda, Masayuki
AU - Inenaga, Shunsuke
AU - Bannai, Hideo
AU - Shinohara, Ayumi
AU - Arikawa, Setsuo
PY - 2003/12/1
Y1 - 2003/12/1
N2 - The classificatory power of a pattern is measured by how well it separates two given sets of strings. This paper gives practical algorithms to find the fixed/variable-length-don't-care pattern (FVLDC pattern) and approximate FVLDC pattern which are most classificatory for two given string sets. We also present algorithms to discover the best window-accumulated FVLDC pattern and window-accumulated approximate FVLDC pattern. All of our new algorithms run in practical amount of time by means of suitable pruning heuristics and fast pattern matching techniques.
AB - The classificatory power of a pattern is measured by how well it separates two given sets of strings. This paper gives practical algorithms to find the fixed/variable-length-don't-care pattern (FVLDC pattern) and approximate FVLDC pattern which are most classificatory for two given string sets. We also present algorithms to discover the best window-accumulated FVLDC pattern and window-accumulated approximate FVLDC pattern. All of our new algorithms run in practical amount of time by means of suitable pruning heuristics and fast pattern matching techniques.
UR - http://www.scopus.com/inward/record.url?scp=0242297806&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0242297806&partnerID=8YFLogxK
M3 - Article
VL - 2843
SP - 486
EP - 493
JO - Lecture Notes in Computer Science
JF - Lecture Notes in Computer Science
SN - 0302-9743
ER -