Title :
Personalized Recommendation Algorithm Research Based on Multi-agent
Author :
Zhu, Hai ; Song, Xiaoli ; Zhang, Shiju ; Gao, Yan ; Zhang, Panke
Author_Institution :
Econ. & Adm. Coll., Henan Univ. of Sci. & Technol., Luoyang
Abstract :
In order to meet the accuracy need of network users on information service, this paper introduces multi- agent feedback learning mechanism based on traditional collaborative filtering algorithms and proposes recommendation algorithm based on multi-agent. During the recommendation process, the algorithm, considering the recommended project as a recommended subject, infers autonomously whether the recommended project fits the target users. Meanwhile, the recommended subject can also improve recommendation precision by active learning based on userpsilas feedback. The recommendation algorithm can be finely applied to library recommender system and partial E-commerce recommender system.
Keywords :
information filtering; multi-agent systems; user interfaces; active learning; collaborative filtering algorithms; e-commerce recommender system; information service; library recommender system; multiagent feedback learning mechanism; network users; personalized recommendation algorithm; recommendation process; user feedback; Collaboration; Databases; Educational institutions; Feedback; Filtering algorithms; History; Internet; Recommender systems; Search engines; Seminars; Multi-agent; Recommendation Engine; User Interest;
Conference_Titel :
Business and Information Management, 2008. ISBIM '08. International Seminar on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3560-9
DOI :
10.1109/ISBIM.2008.69