An Improved Recommendation Method for Better Filtering Information out of Database

• Item type: Trans(1)
• 公開日: 2002-06-15
• タイトル: An Improved Recommendation Method for Better Filtering Information out of Database
• タイトル / 言語: en
• タイトル: An Improved Recommendation Method for Better Filtering Information out of Database
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 研究論文
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Graduate School of Information Systems University of Electro - Communications
• 著者所属: Division of Mathematics & Computer Science Vrije Universiteit Amsterdam the Netherlands
• 著者所属: Graduate School of Information Systems University of Electro - Communications
• 著者所属(英): en
• 著者所属(英): Graduate School of Information Systems, University of Electro - Communications
• 著者所属(英): en
• 著者所属(英): Division of Mathematics & Computer Science, Vrije Universiteit Amsterdam, the Netherlands
• 著者所属(英): en
• 著者所属(英): Graduate School of Information Systems, University of Electro - Communications
• 著者名: Saranya, Maneeroj; Hideaki, Kanai; Katsuya, Hakozaki
• 著者名(英): Saranya, Maneeroj; Hideaki, Kanai; Katsuya, Hakozaki
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Content-based filtering and collaborative filtering techniques have been used for selecting information based on user's previous preference tendency and opinions of other people who have similar tastes with the user.Combining both filtering techniques or hybrid systems have also been proposed to get better recommendation results.In this paper we present an improved recommendation method that copes with the sparsity rating problem and increases the quality of Information Filtering agent of the hybrid systems.This propose is to recommend information that reflect the user interest more accurately. As implementing our method we also present an experimental recommender system for movie called e-Yawara (extended Yawara).The evaluation shows that e-Yawara is more effcient and provides more accurate results than conventional filtering systems both collaborative filtering and hybrid systems.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Content-based filtering and collaborative filtering techniques have been used for selecting information based on user's previous preference tendency and opinions of other people who have similar tastes with the user.Combining both filtering techniques or hybrid systems have also been proposed to get better recommendation results.In this paper,we present an improved recommendation method that copes with the sparsity rating problem and increases the quality of Information Filtering agent of the hybrid systems.This propose is to recommend information that reflect the user interest more accurately. As implementing our method, we also present an experimental recommender system for movie,called e-Yawara (extended Yawara).The evaluation shows that e-Yawara is more effcient and provides more accurate results than conventional filtering systems,both collaborative filtering and hybrid systems.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA11464847
• 書誌情報: 情報処理学会論文誌データベース（TOD）; 巻 43, 号 SIG05(TOD14), p. 66-74, 発行日 2002-06-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7799
• 出版者 / 言語: ja
• 出版者: 情報処理学会