IWTrust: Improving User Trust in Answers from the Web

Question answering systems users may find answers without any supporting information insufficient for determining trust levels. Once those question answering systems begin to rely on source information that varies greatly in quality and depth, such as is typical in web settings, users may trust answers even less. We address this problem by augmenting answers with optional information about the sources that were used in the answer generation process. In addition, we introduce a trust infrastructure, IWTrust, which enables computations of trust values for answers from the Web. Users of IWTrust have access to sources used in answer computation along with trust values for those source, thus they are better able to judge answer trustworthiness. Our work builds upon existing Inference Web components for representing and maintaining proofs and proof related information justifying answers. It includes a new TrustNet component for managing trust relations and for computing trust values. This paper also introduces the Inference Web answer trust computation algorithm and presents an example of its use for ranking answers and justifications by trust.