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    题名: Using emotional context from article for contextual music recommendation
    作者: Chen, Chih-Ming;Tsai, Ming-Feng;Liu, J.-Y.;Yang, Y.-H.
    陳志明;蔡銘峰
    贡献者: 資科系
    关键词: Content-based approach;Context information;Context-aware approaches;Factorization machines;Listening context;Music recommendation;Perceptual dimensions;Quality of recommendations
    日期: 2013-10
    上传时间: 2015-05-28 16:59:41 (UTC+8)
    摘要: This paper proposes a context-aware approach that recommends music to a user based on the user`s emotional state predicted from the article the user writes. We analyze the association between user-generated text and music by using a real-world dataset with <user, text, music> tripartite information collected from the social blogging website LiveJournal. The audio information represents various perceptual dimensions of music listening, including danceability, loudness, mode, and tempo; the emotional text information consists of bag-of-words and three dimensional affective states within an article: valence, arousal and dominance. To combine these factors for music recommendation, a factorization machine- based approach is taken. Our evaluation shows that the emotional context information mined from user-generated articles does improve the quality of recommendation, com- paring to either the collaborative filtering approach or the content-based approach. Copyright © 2013 ACM.
    關聯: MM 2013 - Proceedings of the 2013 ACM Multimedia Conference, 2013, 649-652, 21st ACM International Conference on Multimedia, MM 2013; Barcelona; Spain; 21 October 2013 到 25 October 2013; 類別編號433137; 代碼 100792
    数据类型: conference
    DOI 連結: http://dx.doi.org/10.1145/2502081.2502170
    DOI: 10.1145/2502081.2502170
    显示于类别:[資訊科學系] 會議論文
    [資訊科學系] 會議論文

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