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    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/69139


    Title: A Music Recommendation System Based on Music and User Grouping
    Authors: 陳良弼
    Chen,Hung-Chen;Chen,Arbee L. P.
    Contributors: 資科系
    Keywords: access histories;music recommendation;perceptual properties;recommendation methods;user profiles
    Date: 2005
    Issue Date: 2014-08-21 15:00:24 (UTC+8)
    Abstract: In this paper, we present a music recommendation system, which provides a personalized service of music recommendation. The polyphonic music objects of MIDI format are first analyzed for deriving information for music grouping. For this purpose, the representative track of each polyphonic music object is first determined, and then six features are extracted from this track for proper music grouping. Moreover, the user access histories are analyzed to derive the profiles of user interests and behaviors for user grouping. The content-based, collaborative, and statistics-based recommendation methods are proposed based on the favorite degrees of the users to the music groups, and the user groups they belong to. A series of experiments are carried out to show that our approach performs well.
    Relation: Journal of Intelligent Information Systems,24:2/3,113-132
    Data Type: article
    DOI link: http://dx.doi.org/10.1007/s10844-005-0319-3
    DOI: 10.1007/s10844-005-0319-3
    Appears in Collections:[Department of Computer Science ] Periodical Articles

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