Truth Discovery with Multiple Conflicting Information
Truth Discovery with Multiple Conflicting Information
Providers on the Web.
Abstract:
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 in-formation on a subject, such as different specifications for the same product. In this paper we propose a new problem called Veracity that is 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 Truth Finder, 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. Our experiments show that Truth Finder successfully finds true facts among conflicting information, and identifies trustworthy web sites better than the popular search engines.
Existing System:
▪ Page Rank and Authority-Hub analysis is to utilize the hyperlinks to find pages with high authorities.
▪ These two approaches identifying important web pages that users are interested in, Unfortunately, the popularity of web pages does not necessarily lead to accuracy of information
Proposed System:
▪ We formulate the Veracity problem about how to discover true facts from conflicting information.
▪ Second, we propose a framework to solve this problem, by defining the trustworthiness of websites, confidence of facts, and influences between facts.
▪ Finally, we propose an algorithm called TRUTHFINDER for identifying true facts using iterative methods.
Disadvantage:
▪ The popularity of web pages does not necessarily lead to accuracy of
Providers on the Web.
Abstract:
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 in-formation on a subject, such as different specifications for the same product. In this paper we propose a new problem called Veracity that is 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 Truth Finder, 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. Our experiments show that Truth Finder successfully finds true facts among conflicting information, and identifies trustworthy web sites better than the popular search engines.
Existing System:
▪ Page Rank and Authority-Hub analysis is to utilize the hyperlinks to find pages with high authorities.
▪ These two approaches identifying important web pages that users are interested in, Unfortunately, the popularity of web pages does not necessarily lead to accuracy of information
Proposed System:
▪ We formulate the Veracity problem about how to discover true facts from conflicting information.
▪ Second, we propose a framework to solve this problem, by defining the trustworthiness of websites, confidence of facts, and influences between facts.
▪ Finally, we propose an algorithm called TRUTHFINDER for identifying true facts using iterative methods.
Disadvantage:
▪ The popularity of web pages does not necessarily lead to accuracy of