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The world-wide web has become the most important information source for most of us. Unfortunately, there is no guarantee for the correctness of information on the web. Moreover, different web sites often provide conflicting information on a subject, such as different specifications for the same product. In this paper we propose a new problem called Veracity, i.e., conformity to truth, which studies how to find true facts from a large amount of conflicting information on many subjects that is provided by various web sites. We design a general framework for the Veracity problem, and invent an algorithm called TruthFinder, which utilizes the relationships between web sites and their information, i.e., a web site is trustworthy if it provides many pieces of true information, and a piece of information is likely to be true if it is provided by many trustworthy web sites. An iterative method is used to infer the trustworthiness of web sites and the correctness of information from each other. Our experiments show that TruthFinder successfully finds true facts among conflicting information, and identifies trustworthy web sites better than the popular search engines.
Data mining, Web mining

J. Han, X. Yin and P. S. Yu, "Truth Discovery with Multiple Conflicting Information Providers on the Web," in IEEE Transactions on Knowledge & Data Engineering, vol. 20, no. , pp. 796-808, 2007.
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