政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/69114
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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/69114


    Title: Emotion-based music recommendation by affinity discovery from film music
    Authors: 沈錳坤
    Shan,Man-Kwan;Kuo,Fang-Fei;Meng-Fen Chiang;Suh-Yin Lee
    Contributors: 資科系
    Keywords: Music recommendation;Emotion detection;Affinity discovery
    Date: 2009-05
    Issue Date: 2014-08-21 12:04:43 (UTC+8)
    Abstract: With the growth of digital music, the development of music recommendation is helpful for users to pick desirable music pieces from a huge repository of music. The existing music recommendation approaches are based on a user’s preference on music. However, sometimes, it might better meet users’ requirement to recommend music pieces according to emotions. In this paper, we propose a novel framework for emotion-based music recommendation. The core of the recommendation framework is the construction of the music emotion model by affinity discovery from film music, which plays an important role in conveying emotions in film. We investigate the music feature extraction and propose the Music Affinity Graph and Music Affinity Graph-Plus algorithms for the construction of music emotion model. Experimental result shows the proposed emotion-based music recommendation achieves 85% accuracy in average.
    Relation: Expert Systems with Applications,36(4),7666-7674
    Data Type: article
    DOI link: http://dx.doi.org/10.1016/j.eswa.2008.09.042
    DOI: 10.1016/j.eswa.2008.09.042
    Appears in Collections:[Department of Computer Science ] Periodical Articles

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