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A Personalized Recommendation Algorithm Based on Information Entropy of Social Tags
Received date: 2013-10-08
Revised date: 2013-11-20
Online published: 2013-12-05
Social tags are more and more popular. How to fully make use of social tags is also becoming critically important. However, the quality of tags varies because tags have no fixed structure. Besides, the same tag may play different roles for different people. In this paper, a personalized recommendation algorithm based on social tag information entropy is proposed. In addition, we compare the proposed algorithm information entropy with the classic collaborative filtering, and find the accuracy is significantly improved by 10.9%.
Key words: recommendation algorithm; social tags; information entropy
Wang Jun , Zhang Zike . A Personalized Recommendation Algorithm Based on Information Entropy of Social Tags[J]. Library and Information Service, 2013 , 57(23) : 31 -35 . DOI: 10.7536/j.issn.0252-3116.2013.23.005
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