Presentation 2010-01-22
Reduction technique of user rating histories for information filtering systems
Takayuki UDA, Tetsuo KINOSHITA,
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Abstract(in English) The information filtering system refers to action histories and evaluation histories of the user to perform filtering. If an operation period becomes long, the value of old evaluation histories deteriorates for the preference changes of the user. In this paper, we propose the reduction technique of user rating histories for information filtering systems. By an evaluation experiment, we confirmed that prediction processing time was shortened without the deterioration of a prediction precision and a coverage.
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Keyword(in English) Collaborative Filtering / Prediction processing time / Recommender System / Prediction Accuracy / Coverage
Paper # AI2009-21
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Conference Information
Committee AI
Conference Date 2010/1/15(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) Reduction technique of user rating histories for information filtering systems
Sub Title (in English)
Keyword(1) Collaborative Filtering
Keyword(2) Prediction processing time
Keyword(3) Recommender System
Keyword(4) Prediction Accuracy
Keyword(5) Coverage
1st Author's Name Takayuki UDA
1st Author's Affiliation Secretariat, INSTITUTE of INFORMATION SECURITY()
2nd Author's Name Tetsuo KINOSHITA
2nd Author's Affiliation Cyberscience Center Tohoku University
Date 2010-01-22
Paper # AI2009-21
Volume (vol) vol.109
Number (no) 386
Page pp.pp.-
#Pages 6
Date of Issue