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저자 Sung-Woo Bang, Hye-Wuk Jung, Jaekwang Kim, and Jee-Hyong Lee 
학회명 International Symposium on Advanced Intelligent Systems 
학회명 (약자) ISIS 2009 
pp. 51-54 
학회시작일 2009-08-17 
학회종료일 2009-08-19 
비고  
The rise of music resources has led to a parallel rise in the need to manage thousands of songs on user devices. User playlists, especially, expect to be generated automatically, because the manual selection of songs for creating playlist is a troublesome work. This paper proposes an auto playlist recommendation system considering user preferences and context of use. This system has two separated systems; 1) mood and emotion classification system and 2) music recommendation system. Users need to choose just one seed song for reflecting their preference and context of use. Then system recommends candidate song list before the current song ends in order to fill up user playlist. User also can remove unsatisfied songs from recommended song list to adapt user preferences of the system for the next song list. The generated playlists show well defined mood and emotion of music and provide songs that user preferences are reflected.

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