標題: Evaluating subjective compositions by the cooperation between human and adaptive agents
作者: Huang, Chung-Yuan
Hsieh, Ji-Lung
Sun, Chuen-Tsai
Cheng, Chia-Ying
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: 2006
摘要: We describe a music recommender model that uses intermediate agents to evaluate music composition according to their own rules respectively, and make recommendations to user. After user scoring recommended items, agents can adapt their selection rules to fit user tastes, even when user preferences undergo a rapid change. Depending on the number of users, the model can also be applied to such tasks as critiquing large numbers of music, image, or written compositions in a competitive contest with other judges. Several experiments are reported to test the model\'s ability to adapt to rapidly changing conditions yet still make appropriate decisions and recommendations.
URI: http://hdl.handle.net/11536/136533
ISBN: 978-3-540-49026-5
ISSN: 0302-9743
期刊: MICAI 2006: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS
Volume: 4293
起始頁: 974
結束頁: +
Appears in Collections:Conferences Paper