期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2017
卷号：6
期号：7
页码：15371
DOI：10.15680/IJIRSET.2017.0607375
出版社：S&S Publications
摘要：Reputation-based trust models are widely used in e-Commerce applications and feedback ratings areaggregated to compute sellers’ reputation trust scores. The “all good reputation” problem, however, is prevalent incurrent reputation systems reputation scores are universally high for sellers and it is difficult for potential buyers toselect trustworthy sellers. In this paper, based on the observation that buyers often express opinions openly in free textfeedback comments, we propose. CommTrust for trust evaluation by mining feedback comments. Our maincontributions include: 1) we propose a multidimensional trust model for computing reputation scores from userfeedback comments; and 2) we propose an algorithm for mining feedback comments for dimension ratings and weights,combining techniques of natural language processing, opinion mining, and topic modelling. Extensive experiments oneBay and Amazon data demonstrate that CommTrust can effectively address the “all good reputation” issue and ranksellers effectively. To the best of our knowledge, our research is the first piece of work on trust evaluation by miningfeedback comments.
关键词：K.4.4 Electronic commerce; H.2.8.I Text mining.
