Volume 8 Number 2 (Feb. 2013)
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JSW 2013 Vol.8(2): 357-360 ISSN: 1796-217X
doi: 10.4304/jsw.8.2.357-360

A Recommendation Trust Method Based on Fuzzy Clustering in P2P Networks

Liangmin Guo, Yonglong Luo, Zhengzhen Zhou, Meijing Ji

Department of Computer Science and Technology, Engineering Technology Research Center of Network and Information Security, Anhui Normal University, Wuhu, China

Abstract—In this paper, we apply the thought of maximal tree to propose a peer classification method. It’s based on fuzzy clustering. The method classifies effectively the recommendation peers according to their trusted level. Finally, the experiment results show that if you choose the recommendation peers with higher trusted level, their recommendation result will be more truthful and reliable. So our method can effectively avoid false recommendation, and enhance the accuracy of trust evaluation in P2P networks.

Index Terms—Fuzzy clustering, thought of maximum tree, recommendation trust, recommendation peer.

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Cite: Liangmin Guo, Yonglong Luo, Zhengzhen Zhou, Meijing Ji, "A Recommendation Trust Method Based on Fuzzy Clustering in P2P Networks," Journal of Software vol. 8, no. 2, pp. 357-360, 2013.

General Information

  • ISSN: 1796-217X (Online)
  • Frequency:  Quarterly
  • Editor-in-Chief: Prof. Antanas Verikas
  • Executive Editor: Ms. Yoyo Y. Zhou
  • Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
  • E-mail: jsweditorialoffice@gmail.com
  • APC: 500USD
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