Trust analysis with clustering

Web provides rich information about a variety of objects. Trustability is a major concern on the web. Truth establishment is an important task so as to provide the right information to the user from the most trustworthy source. Trustworthiness of information provider and the confidence of the facts it provides are inter-dependent on each other and hence can be expressed iteratively in terms of each other. However, a single information provider may not be the most trustworthy for all kinds of information. Every information provider has its own area of competence where it can perform better than others. We derive a model that can evaluate trustability on objects and information providers based on clusters (groups). We propose a method which groups the set of objects for which similar set of providers provide "good" facts, and provides better accuracy in addition to high quality object clusters.