Employing Locally Linear Neuro-Fuzzy Model for Trust Prediction
Publish place: Fourth International Conference on Web Research
Publish Year: 1397
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
IRANWEB04_013
تاریخ نمایه سازی: 24 شهریور 1397
Abstract:
Trust network can be useful tool for identification of the trustful sources of information in a social web application. Despite the usefulness of a trust network, it is usually sparse as users are generally reluctant to express the trust relationships. Therefore, one approach to make the trust network denser is to identify the potential trust relationships between users and recommend the reliable and trustful participant to users. The main contribution of this research is the examination of the performance of Locally Linear Neuro Fuzzy (LLNF) model in the trust prediction context. Therefore, LLNF was compared with two classification techniques including ANFIS and C4.5 decision tree. To conduct experiments, data of Epinions network were used. The results of experiments demonstrate that LLNF achieves the highest performance in terms of area under ROC (AUC). In addition, LLNF follows closely C4.5 decision tree regarding F- measure. LLNF can be a good candidate for trust relationships prediction
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Authors
Hossein Abbasimehr
Assistant professor, Faculty of Information Technology and Computer Engineering Azarbaijan Shahid Madani University Tabriz, Iran