DocumentCode :
460824
Title :
Using Evolving Agents to Critique Subjective Music Compositions
Author :
Sun, Chuen-Tsai ; Hsieh, Ji-Lung ; Huang, Chung-Yuan
Author_Institution :
Dept. of Comput. Sci., Nat. Chiao Tung Univ., Hsinchu
Volume :
1
fYear :
2006
fDate :
Nov. 2006
Firstpage :
474
Lastpage :
480
Abstract :
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
Keywords :
evolutionary computation; information filtering; multi-agent systems; music; interactive evolutionary computing; music composition; music recommender model; Books; Collaboration; Computer science; Feature extraction; History; Information filtering; Information filters; Mood; Motion pictures; Recommender systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security, 2006 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
1-4244-0605-6
Electronic_ISBN :
1-4244-0605-6
Type :
conf
DOI :
10.1109/ICCIAS.2006.294180
Filename :
4072133
Link To Document :
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