標題: Using evolving agents to critique subjective music compositions
作者: Sun, Chuen-Tsai
Hsieh, Ji-Lung
Huang, Chung-Yuan
資訊工程學系
Department of Computer Science
關鍵字: music recommender system;interactive evolutionary computing;adaptive agent;critiquing subjective data;content-based filtering
公開日期: 2007
摘要: The authors describe a recommender model that uses intermediate agents to evaluate a large body of subjective data according to a set of rules and make recommendations to users. After scoring recommended items, agents adapt their own selection rules via interactive evolutionary computing to fit user tastes, even when user preferences undergo a rapid change. The model can be applied to such tasks as critiquing large numbers of music or written compositions. In this paper we use musical selections to illustrate how agents make recommendations and report the results of several experiments designed to test the model\'s ability to adapt to rapidly changing conditions yet still make appropriate decisions and recommendations.
URI: http://hdl.handle.net/11536/134463
ISBN: 978-3-540-74376-7
ISSN: 0302-9743
期刊: COMPUTATIONAL INTELLIGENCE AND SECURITY
Volume: 4456
起始頁: 336
結束頁: +
顯示於類別:會議論文