Effective browsing technique based on behavioral collaborative filtering on social streams

研究成果: ジャーナルへの寄稿Conference article

抄録

In recent years, Social Networking Services (SNSs) are growing in popularity, and generating new articles moment by moment. However, when huge article streams are delivered from the SNS, it is not easy to browse them efficiently because users would sometimes skip valuable articles. In this paper, we propose a method to recommend an unread article in order to achieve efficient browsing. Our method estimates the preference of a user on a delivered article based on the browsing behavior of the user, and predicts the preference of each unread article based on the collaborative filtering approach. Our system estimates the value of each unread article for the target user based on the behaviors of users who might be highly similar to the target user's behavior of reading articles, and utilizes the estimation results for composing unread articles into a stream in an appropriate order to realize efficient browsing.

元の言語英語
ページ(範囲)1702-1710
ページ数9
ジャーナルProcedia Computer Science
35
発行部数C
DOI
出版物ステータス出版済み - 1 1 2014
イベントInternational Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2014 - Gdynia, ポーランド
継続期間: 9 15 20149 17 2014

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Collaborative filtering

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

これを引用

Effective browsing technique based on behavioral collaborative filtering on social streams. / Yan, Hong; Ushiama, Taketoshi.

:: Procedia Computer Science, 巻 35, 番号 C, 01.01.2014, p. 1702-1710.

研究成果: ジャーナルへの寄稿Conference article

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