An Advanced Movie Recommender System Based on High-Quality Neighbors

• Item type: Trans(1)
• 公開日: 2005-03-15
• タイトル: An Advanced Movie Recommender System Based on High-Quality Neighbors
• タイトル / 言語: en
• タイトル: An Advanced Movie Recommender System Based on High-Quality Neighbors
• 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: Graduate School of Information Systems University of Electro-Communications
• 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): 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
• 著者名: Saranya, Maneeroj; Yuka, Kato; Katsuya, Hakozaki
• 著者名(英): Saranya, Maneeroj; Yuka, Kato; Katsuya, Hakozaki
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: This paper proposes an advanced movie recommender system. The system is primarily based on the content-based collaborative filtering or hybrid filtering technique. The distinctive point of this system lies in an improved neighborhood formation method in order to get highquality neighbors. Current hybrid systems only use user’s opinions as user’s rating values in selecting neighbors. That causes loss of user preference features and tends to provide poor quality neighbors. The proposed system uses the user’s opinions on various features of user preferences in selecting neighbors. That results in high-quality neighbors and high-quality recommendations will be obtained accordingly. An experimental movie recommender system called Advanced Yawara system has been developed to prove the effectiveness of the method. The evaluation results show that the Advanced Yawara system provides higher quality of recommendations than current hybrid systems.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: This paper proposes an advanced movie recommender system. The system is primarily based on the content-based collaborative filtering or hybrid filtering technique. The distinctive point of this system lies in an improved neighborhood formation method in order to get highquality neighbors. Current hybrid systems only use user’s opinions as user’s rating values in selecting neighbors. That causes loss of user preference features, and tends to provide poor quality neighbors. The proposed system uses the user’s opinions on various features of user preferences in selecting neighbors. That results in high-quality neighbors and high-quality recommendations will be obtained accordingly. An experimental movie recommender system, called Advanced Yawara system has been developed to prove the effectiveness of the method. The evaluation results show that the Advanced Yawara system provides higher quality of recommendations than current 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 46, 号 SIG5(TOD25), p. 28-39, 発行日 2005-03-15
• 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