Presentation 2009-05-22
A Method for Relevance Calculation between Browsed Web Pages toward Personalized Recommendation System
Kosuke NAKAO, Tsunenori MINE,
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Abstract(in English) This thesis proposes "Relative-Webpage-Recommendation" as a support of browsing. Using this method, user can get webpages that has relevance to browsing one. And we think that this method provides more personalized web browsing. Relevance between webpages is calculated from user's browsing history. In this thesis, we propose the method for calculating relevance from two elements. One is that user's browsing history is mappable to forest structure. Another is a hypothesis that there is some co-occurrence between pages which browsed at the same time by tab browser. Additionally, we consider experimental result, and show issue.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) information recommendation / personalization / browsing support / multi agent / co-occurrence between tab
Paper # AI2009-6
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Committee AI
Conference Date 2009/5/15(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) A Method for Relevance Calculation between Browsed Web Pages toward Personalized Recommendation System
Sub Title (in English)
Keyword(1) information recommendation
Keyword(2) personalization
Keyword(3) browsing support
Keyword(4) multi agent
Keyword(5) co-occurrence between tab
1st Author's Name Kosuke NAKAO
1st Author's Affiliation Kyushu University, Graduate School of Information Science & Electrical Engineering()
2nd Author's Name Tsunenori MINE
2nd Author's Affiliation Kyushu University, Graduate School of Information Science & Electrical Engineering
Date 2009-05-22
Paper # AI2009-6
Volume (vol) vol.109
Number (no) 51
Page pp.pp.-
#Pages 6
Date of Issue