Presentation 2001/7/16
Discovery of Maximally Frequent Tag Tree Patterns in Semistructured Data
Tetsuhiro Miyahara, Takayoshi Shoudai, Tomoyuki Uchida, Kenichi Takahashi, Hiroaki Ueda,
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Abstract(in English) Many documents such as Web documents or XML files have no rigid structure. We propose a new method for discovering frequent tree structured patterns in such semistructured Web documents. We consider data mining problems of finding maximally frequent tag tree patterns in semistructured data such as Web documents. A tag tree pattern is an edge labeled tree which has structured variables. An edge label is a tag or a keyword in Web documents, and a variable can be substituted by arbitrary tree.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) knowledge discovery / Web mining / semistructured data / XML file / tag tree pattern
Paper # OFS2001-7,AI2001-12
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Committee AI
Conference Date 2001/7/16(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) Discovery of Maximally Frequent Tag Tree Patterns in Semistructured Data
Sub Title (in English)
Keyword(1) knowledge discovery
Keyword(2) Web mining
Keyword(3) semistructured data
Keyword(4) XML file
Keyword(5) tag tree pattern
1st Author's Name Tetsuhiro Miyahara
1st Author's Affiliation Faculty of Information Sciences, Hiroshima City University()
2nd Author's Name Takayoshi Shoudai
2nd Author's Affiliation Department of Informatics, Kyushu University
3rd Author's Name Tomoyuki Uchida
3rd Author's Affiliation Faculty of Information Sciences, Hiroshima City University
4th Author's Name Kenichi Takahashi
4th Author's Affiliation Faculty of Information Sciences, Hiroshima City University
5th Author's Name Hiroaki Ueda
5th Author's Affiliation Faculty of Information Sciences, Hiroshima City University
Date 2001/7/16
Paper # OFS2001-7,AI2001-12
Volume (vol) vol.101
Number (no) 210
Page pp.pp.-
#Pages 6
Date of Issue