Hybrid recommender system based on fuzzy clustering and collaborative filtering

Author

Verma, S.K. ; Mittal, Natasha ; Agarwal, Basant

Author_Institution

Dept. of Comput. Eng., Malaviya Nat. Inst. of Technol., Jaipur, India

fYear

2013

fDate

20-22 Sept. 2013

Firstpage

116

Lastpage

120

Abstract

Recommender systems have achieved widespread success for e-commerce companies. Significant growth of customers and products poses key challenges for recommender system namely sparsity and scalability. In this paper, a hybrid system is proposed that is capable of handling these issues that is based on collaborative filtering and fuzzy c-means clustering algorithms. Experimental results show the effectiveness of the proposed recommender system.

Keywords

collaborative filtering; electronic commerce; fuzzy set theory; pattern clustering; recommender systems; collaborative filtering; e-commerce companies; fuzzy c-means clustering algorithms; hybrid recommender system; scalability; sparsity; Clustering algorithms; Collaboration; Computers; Motion pictures; Prediction algorithms; Recommender systems; Collaborative Filtering; Fuzzy Clustering (FCM); Recommender System;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Communication Technology (ICCCT), 2013 4th International Conference on

Conference_Location

Allahabad

Print_ISBN

978-1-4799-1569-9

Type

conf

DOI

10.1109/ICCCT.2013.6749613

Filename

6749613

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3402214