A unified model for unsupervised opinion spamming detection incorporating text generality?
Refereed conference paper presented and published in conference proceedings


全文

其它資訊
摘要Many existing methods on review spam detection considering text content merely utilize simple text features such as content similarity. We explore a novel idea of exploiting text generality for improving spam detection. Besides, apart from the task of review spam detection, although there have also been some works on identifying the review spammers (users) and the manipulated offerings (items), no previous works have attempted to solve these three tasks in a unified model. We have proposed a unified probabilistic graphical model to detect the suspicious review spams, the review spammers and the manipulated offerings in an unsupervised manner. Experimental results on three review corpora including Amazon, Yelp and TripAdvisor have demonstrated the superiority of our proposed model compared with the state-of-the-art models.
著者Xu Y., Shi B., Tian W., Lam W.
會議名稱24th International Joint Conference on Artificial Intelligence, IJCAI 2015
會議開始日25.07.2015
會議完結日31.07.2015
會議地點Buenos Aires
會議國家/地區阿根廷
出版年份2015
月份1
日期1
卷號2015-January
頁次725 - 732
國際標準書號9781577357384
國際標準期刊號1045-0823
語言英式英語

上次更新時間 2020-06-09 於 00:54