Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Neighborhood Formation and Anomaly Detection in Bipartite Graphs
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Discovering Contexts and Contextual Outliers Using Random Walks in Graphs
ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
Fair news reader: recommending news articles with different sentiments based on user preference
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Detecting product review spammers using rating behaviors
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
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A number of methods have been proposed for detecting spam reviews in order to obtain credible summaries. These methods, however, could not be uniformly applied to various forms of reviews and are not suitable for a product or service which has been evaluated by few reviewers. In this paper, we propose a bipartite graph model of review sites and a mutually reinforcing method of summarizing evaluations and detecting anomalous reviewers. Our model and method can be applied to reviews of various forms, and is suitable for a subject with few reviewers. We ascertain the effectiveness of our method using reviews of three forms on Yahoo! Movie web site.