Presentation 2003/9/7
Macro View Approach to Discovered Rule Filtering
Yasuhiko KITAMURA, Akira IIDA, Keunsik PARK, Shoji TATSUMI,
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Abstract(in English) A data mining system can semi-automatically discover knowledge by mining a large volume of data, but the discovered knowledge is not always novel and interesting to the user. We have proposed a discovered rule filtering method to filter rules discovered by a data mining system to be novel and interesting to the user by using information retrieval technique. In this method, we rank discovered rules according to the results of information retrieval from the Internet. In this paper, we show two approaches toward discovered rule filtering; micro view approach and macro view approach, and mainly discuss the latter. Our macro view approach utilizes the yearly trend of Jaccard coefficient and judges whether a discovered rule is a hot topic or not. By using a concrete example of clinical data mining and MEDLINE document retrieval, we show advantages of macro view approaches toward discovered rule filtering.
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Keyword(in English) discovered rule filtering / data mining / information retrieval / MEDLINE database / macro view approach / Jaccard coefficient
Paper # AI2003-31
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Committee AI
Conference Date 2003/9/7(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Macro View Approach to Discovered Rule Filtering
Sub Title (in English)
Keyword(1) discovered rule filtering
Keyword(2) data mining
Keyword(3) information retrieval
Keyword(4) MEDLINE database
Keyword(5) macro view approach
Keyword(6) Jaccard coefficient
1st Author's Name Yasuhiko KITAMURA
1st Author's Affiliation School of Science and Technology, Kwansei Gakuin University()
2nd Author's Name Akira IIDA
2nd Author's Affiliation Graduate School of Engineering, Osaka City University
3rd Author's Name Keunsik PARK
3rd Author's Affiliation Graduate School of Medicine, Osaka City University
4th Author's Name Shoji TATSUMI
4th Author's Affiliation Graduate School of Engineering, Osaka City University
Date 2003/9/7
Paper # AI2003-31
Volume (vol) vol.103
Number (no) 304
Page pp.pp.-
#Pages 6
Date of Issue