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New Technology of Library and Information Service  2012, Vol. 28 Issue (3): 35-39    DOI: 10.11925/infotech.1003-3513.2012.03.06
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An Improved Collaborative Filtering Recommendation Algorithm Based on Vague Sets Theory
Zhang Huiying1, Xue Fuliang1,2
1. College of Management & Economics, Tianjin University, Tianjin 300072, China;
2. Business School, Tianjin University of Finance & Economics, Tianjin 300222, China
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Abstract  Aiming at the difficulty of project features expression,this paper brings forward to extract and represent it with vague sets theory.Then similar item is clustered to predict missing evaluation values of item, thus eliminating the sparsity problem of collaborative filtering recommendation. Based on the predicted rating matrix,similar users are clustered,and collaborative filtering recommendation is implemented in the space of item cluster to give more targeted recommendation. Evaluation results show that the proposed method is more effective both in the accuracy and in relevance of recommendations.
Key wordsRecommender system      Collaborative filtering      Item similarity      Content-based recommendation      Vague sets     
Received: 06 January 2012      Published: 19 April 2012



Cite this article:

Zhang Huiying, Xue Fuliang. An Improved Collaborative Filtering Recommendation Algorithm Based on Vague Sets Theory. New Technology of Library and Information Service, 2012, 28(3): 35-39.

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