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Predicting Uninteresting Information in Interesting Genre with Similar-preference Users |
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2nd International Conference on Software Engineering, Management & Application |
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© 2011 by OLS Journal - ISSN No : 2091-
0266 |
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Number 1 Article 1 |
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Year of Publication : 2011 |
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Authors : Tsukasa Kondo, Masaya Ito, Fumiko Harada, Hiromitsu Shimakawa |
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Citation |
Tsukasa Kondo, Masaya Ito, Fumiko Harada, Hiromitsu Shimakawa - Predicting Uninteresting Information in Interesting Genre with Similar-preference Users: OLS Journals Special Isssue on Software Engineering, Management & Application 1-2 , 2011 , Published by : OLS Journals , The society Association of Scientists, Developers and Faculties (ASDF) |
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Abstract |
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Almost all existing recommendation systems extract an indicator for recommendation from the information that user judged to be interesting. However, information recommended in this way is not always interesting to the user because recommendation systems cannot exclude the uninteresting information for the target user from the recommendation candidate information. In this paper, we propose a method to extract the web pages which is uninteresting for the target user among the pages matching his interesting genre, excluding uninteresting web pages to him. The condition that the web page is uninteresting for the target user is referred to as “the web page that the target user does not bookmark while many similar-preference users do”. We refer those web pages as to a potential uninteresting web page for the target user. We exclude the web pages which is uninteresting for the target user from the recommendation candidate information. From result of an experiment, we have verified the validity of the condition that the web page uninteresting to the target user. |
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Keywords |
:component; recommendation system; uninteresting information; similar-preference user; |
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