Please use this identifier to cite or link to this item:
Title: An Affective Music Recommendation System
Authors: Pon, Aura
Sharlin, Ehud
Eagle, David
Keywords: Music recommendation
Issue Date: 22-Dec-2010
Abstract: Given that the affective features of music are often the most relevant criteria in selecting music, we propose in this abstract that a music database should be able to be categorized according to its affective influence, and likewise, music recommendations made with consideration to the user’s current affective state. This can be made possible using pre-existing emotion-measuring technology with new algorithms for selecting music with appropriate affective influence, as proven by several studies. An affective music recommender system could avoid many of the inadequacies of traditional recommender systems.
Appears in Collections:Sharlin, Ehud

Files in This Item:
File Description SizeFormat 
2010-988-37.pdf135.05 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.