Computer Science ›› 2018, Vol. 45 ›› Issue (8): 146-150.doi: 10.11896/j.issn.1002-137X.2018.08.026

• Information Security • Previous Articles     Next Articles

Trust Network Based Collaborative Filtering Recommendation Algorithm

ZHANG Hong-bo, WANG Jia-lei, ZHANG Li-juan, LIU Zhi-hong   

  1. School of Cyber Engineering,Xidian University,Xi’an 710071,China
  • Received:2017-01-06 Online:2018-08-29 Published:2018-08-29

Abstract: The problems of data sparsity and cold start cannot be solved by the classical collaborative filtering recommendation schemes.Although these problems can be solved effectively by exploiting the trust networks of users,the performance of these schemes need to be improved.Based on the ubiquitous phenomenon of“if a trusts b,then the similarity between a and b is relatively high”,this paper proposed a collaborative filtering recommendation algorithm,which exploits a penalty and reward mechanism to further promote its performance.Then it was compared with the classical collaborative filtering algorithms and the existing trust recommendation algorithms in terms of the coverage and accuracy.The results show that the performance of the proposed algorithm is improved.

Key words: Recommendation system, Trust network, Collaborative filtering, Cold start

CLC Number: 

  • TP393
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