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| Survey of Recommendation Based on Collaborative Filtering |
| LENG Ya-Jun1, LU Qing1, LIANG Chang-Yong2,3 |
1College of Economics and Management, Shanghai University of Electric Power, Shanghai 201300
2School of Management, Hefei University of Technology, Hefei 230009
3Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei University of Technology, Hefei 230009 |
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Abstract Collaborative filtering is a widely used technique in recommender systems. Extensive studies are carried out on collaborative filtering. However, systematic summary of this field is scarce. In this paper, research of collaborative filtering is reviewed. The meaning and key issues of collaborative filtering, including sparsity, multiple-content and scalability, are described firstly, and then the solutions to the above key issues are introduced in detail. Finally, the future work of collaborative filtering is pointed out. The knowledge framework of collaborative filtering is introduced. It makes the research clues of collaborative filtering clear, provides a reference to other scholars, and improves the performance of personalized information services.
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Received: 06 November 2013
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2014, Vol. 27 
