DocumentCode :
2381385
Title :
A Personalized Recommender Algorithm Based on Fuzzy Relation Reputation Model
Author :
Fang, Meiyu ; Zheng, Xiaolin ; Chen, Deren
Author_Institution :
Coll. of Comput. Sci., Zhejiang Univ., Hangzhou, China
fYear :
2011
fDate :
25-27 May 2011
Firstpage :
193
Lastpage :
197
Abstract :
For overcoming the problems that the traditional collaborative filtering personalized recommender algorithm which called KNN has such as cold-starting, data sparsity, flexibility and black box, a new personalized recommender algorithm based on fuzzy reputation model(called FRPRA) is proposed. We analyze the steps of FRPRA and the differences between it and KNN, explore the ways how FRPRA overcomes the existed problems of KNN. At the same time, we compare the performance of this two algorithms.
Keywords :
electronic commerce; fuzzy set theory; groupware; pattern recognition; recommender systems; KNN; collaborative filtering; electronic commerce; fuzzy relation reputation model; k-nearest neighbor; personalized recommender algorithm; Catalogs; Collaboration; Computer science; Educational institutions; History; Indexes; Pragmatics; Fuzzy Reputation Modeling; KNN; Personalized Recommender Algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Service Sciences (IJCSS), 2011 International Joint Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4577-0326-3
Electronic_ISBN :
978-0-7695-4421-2
Type :
conf
DOI :
10.1109/IJCSS.2011.45
Filename :
5960318
Link To Document :
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