A Novel Trust Evaluation Mechanism for Collaborative Filtering Recommender Systems
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 p...
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| Online Access: | https://ieeexplore.ieee.org/document/8472801/ |
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doaj-9251793322cb4bc782fd9ec852478d7f2021-03-29T21:34:35ZengIEEEIEEE Access2169-35362018-01-016702987031210.1109/ACCESS.2018.28716818472801A Novel Trust Evaluation Mechanism for Collaborative Filtering Recommender SystemsYang Xiao0https://orcid.org/0000-0003-1410-0486Qingqi Pei1https://orcid.org/0000-0001-7614-1422Xuefeng Liu2Shui Yu3https://orcid.org/0000-0003-4485-6743State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an, ChinaState Key Laboratory of Integrated Services Networks, Xidian University, Xi’an, ChinaSchool of Cyber Engineering, Xidian University, Xi’an, ChinaSchool of Software, University of Technology Sydney, Ultimo, NSW, AustraliaIn 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 do not 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, and 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 to the ratings of trusted users. The experimental 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.https://ieeexplore.ieee.org/document/8472801/High trust value entitiesonline social networksrecommendationtrust computation |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Yang Xiao Qingqi Pei Xuefeng Liu Shui Yu |
| spellingShingle |
Yang Xiao Qingqi Pei Xuefeng Liu Shui Yu A Novel Trust Evaluation Mechanism for Collaborative Filtering Recommender Systems IEEE Access High trust value entities online social networks recommendation trust computation |
| author_facet |
Yang Xiao Qingqi Pei Xuefeng Liu Shui Yu |
| author_sort |
Yang Xiao |
| title |
A Novel Trust Evaluation Mechanism for Collaborative Filtering Recommender Systems |
| title_short |
A Novel Trust Evaluation Mechanism for Collaborative Filtering Recommender Systems |
| title_full |
A Novel Trust Evaluation Mechanism for Collaborative Filtering Recommender Systems |
| title_fullStr |
A Novel Trust Evaluation Mechanism for Collaborative Filtering Recommender Systems |
| title_full_unstemmed |
A Novel Trust Evaluation Mechanism for Collaborative Filtering Recommender Systems |
| title_sort |
novel trust evaluation mechanism for collaborative filtering recommender systems |
| publisher |
IEEE |
| series |
IEEE Access |
| issn |
2169-3536 |
| publishDate |
2018-01-01 |
| description |
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 do not 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, and 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 to the ratings of trusted users. The experimental 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. |
| topic |
High trust value entities online social networks recommendation trust computation |
| url |
https://ieeexplore.ieee.org/document/8472801/ |
| work_keys_str_mv |
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