Presentation 2003/3/7
Discovered Rule Filtering System Using MEDLINE Information Retrieval
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 propose a discovered rule filtering method to filter rules discovered by a data mining system and to produce ones that are novel and interesting to the user by using information retrieval technique. In this method, we rank discovered rules according to results of information retrieval from the Internet. In this paper, firstly we show the steps of discovered rule filtering by using a concrete example of clinical data mining and MEDLINE document retrieval. Secondly, we show a prototype system to filter rules discovered by a hepatitis data mining. Lastly, we discuss micro and macro view approaches to discovered rule filtering.
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Keyword(in English) discovered rule filtering / data mining / information retrieval / relevance feedback / MEDLINE database
Paper # AI2002-71
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Committee AI
Conference Date 2003/3/7(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) Discovered Rule Filtering System Using MEDLINE Information Retrieval
Sub Title (in English)
Keyword(1) discovered rule filtering
Keyword(2) data mining
Keyword(3) information retrieval
Keyword(4) relevance feedback
Keyword(5) MEDLINE database
1st Author's Name Yasuhiko KITAMURA
1st Author's Affiliation Graduate School of Engineering, Osaka City 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 2003/3/7
Paper # AI2002-71
Volume (vol) vol.102
Number (no) 710
Page pp.pp.-
#Pages 6
Date of Issue