Presentation 2007-05-31
Finding Commom and Frequent Tree Patterns from Semi-Structured Texts Compressed by a Tree Grammar Compression Method
Seiji MURAKAMI, Koichiro DOI, Akihiro YAMAMOTO,
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Abstract(in English) In this study, we present an algorithm that solves the problem of finding common tree patterns from semi-structured texts compressed by the TGCA algorithm. The algorithm shows that compressing texts by TGCA contributes to the efficiency in solving the problem. In the method, the number of common tree patterns that appear is counted while considering subsumption relations among tree patterns. This study combines two significant studies in semi-structured data, methods for compressing semi-structured data and methods for discovering knowledge from semi-structured data.
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Keyword(in English) semi-structured data / data compression / common pattern discovery / ordered tree patterns
Paper # AI2007-8
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Committee AI
Conference Date 2007/5/24(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Finding Commom and Frequent Tree Patterns from Semi-Structured Texts Compressed by a Tree Grammar Compression Method
Sub Title (in English)
Keyword(1) semi-structured data
Keyword(2) data compression
Keyword(3) common pattern discovery
Keyword(4) ordered tree patterns
1st Author's Name Seiji MURAKAMI
1st Author's Affiliation Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University()
2nd Author's Name Koichiro DOI
2nd Author's Affiliation Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University
3rd Author's Name Akihiro YAMAMOTO
3rd Author's Affiliation Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University
Date 2007-05-31
Paper # AI2007-8
Volume (vol) vol.107
Number (no) 78
Page pp.pp.-
#Pages 6
Date of Issue