Though electronic commerce companies adopt multifarious reputation evaluation mechanisms to guarantee trust between customers and sellers(or customers and platforms),these reputation evaluation systems are still frequently attacked.These attacks have led the reputation ranking and recommendation rankings of sellers to be manipulated.Therefore,large numbers of honest consumers are misled to purchase low quality products.It has been mentioned that overall consideration of trust and distrust information can improve customers ability in defensing against reputation attacks.However,existing works have limitations such as“the trust information and distrust information are less fused”,“one advisor list is used in evaluating all sellers”,which leads to the lack of pertinence and inaccuracy of sellers reputation evaluation.We propose a new defensing strategy called T&D.This strategy considers the trustworthy facet as well as the untrustworthy facet of customers.In addition,this strategy offers a whitelist(which stores several most trustworthy reviewers)and a blacklist(which stores several most untrustworthy reviewers)for customers.Based on the whitelist that is purified using the blacklist,honest customers can find the most trustworthy buyers and evaluate the candidate sellers according to its own experience and ratings of these trustworthy reviewers.Simulated experimental results show that our proposed strategy significantly outperforms state-of-the-art baselines in evaluation accuracy and stability.
Journal of Computer Research and Development
Ma Haiyan , born in 1990. Received his BS and MS degrees from Shandong University of Science and Technology, Shandong, China. His main research interests include artificial intelligence and intelligent business information processing;Liang Yongquan , born in 1967. Professor of the College of Computer Science and Engineering in Shandong University of Science and Technology. Received his PhD degree from the Institute of Computing Technology, Chinese Academy of Sciences. Director of Chinese Association for Artificial Intelligence, senior member of CCF, executive director of Shandong Province Computer Society, vice president of Qingdao Computer Society. His main research in-terests include distributed artificial intelli-gence, data mining, machine learning and multimedia information intelligent processing (firstname.lastname@example.org);Ji Shujuan , born in 1977. Associate professor of the College of Computer Science and Engineering in Shandong University of Science and Technology. Received her BS, MS and PhD degrees in computer software and theory from Shandong University of Science and Technology, Qingdao, China. Her main research interests include artificial intelligence and intelligent business informa-tion processing.通信作者 :纪淑娟(email@example.com);Li Da , born in 1993. Master candidate of Shandong University of Science and Tech-nology. Received his bachelor degree from Qingdao University of Science and Tech-nology, Shandong, China in 2016. His main research interests include artificial intelligence and intelligent business infor-mation processing (firstname.lastname@example.org).