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