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A novel trust evaluation mechanism for collaborative filtering recommender systems

Version 2 2024-06-04, 06:38
Version 1 2018-10-26, 15:35
journal contribution
posted on 2024-06-04, 06:38 authored by Y Xiao, Q Pei, X Liu, S Yu
OAPA In online social networks (OSNs), high trust value entities play an important role in service recommendation when users inquire certain service. Generally, users in OSNs are more willing to choose those services recommended by high trust value entities. In fact, users may suffer from great loss of property once they accept some bad services provided by high trust value entities. However, current schemes don’t consider this problem. Hence we propose a scheme called RHT (recommendation from high trust value entities) to evaluate the trust degree of service recommended by high trust value entities. To be specific, there exist other users who provide their ratings to the service recommended by a high trust value entity, RHT first selects the trusted ones from those users by computing the similarity between target user and them. Simultaneously, RHT also withstands malicious attacks during the trusted nodes selection. In addition, we also design an adaptive trust computation method to calculate trust value according the ratings of trusted users. The experiment results show that RHT has higher accuracy in trust evaluation compared with current representative schemes and do effectively resistant four common attacks when choosing trusted nodes.

History

Journal

IEEE access

Volume

6

Pagination

70298-70312

Location

Piscataway, N.J.

Open access

  • Yes

eISSN

2169-3536

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2018, IEEE

Publisher

IEEE

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