Generalized fact-finding

13 years 1 months ago
Generalized fact-finding
Once information retrieval has located a document, and information extraction has provided its contents, how do we know whether we should actually believe it? Fact-finders are a state-of-the-art class of algorithms that operate in a manner analogous to [2]’s Hubs and Authorities, iteratively computing the trustworthiness of an information source as a function of the believability of the claims it makes, and the believability of a claim as a function of the trustworthiness of those sources asserting it. However, as fact-finders consider only “who claims what”, they ignore a great deal of relevant background and contextual information. We present a framework for “lifting” (generalizing) the fact-finding process, allowing us to elegantly incorporate knowledge such as the confidence of the information extractor and the attributes of the information sources. Experiments demonstrate that leveraging this information significantly improves performance over existing,“unlifted...
Jeff Pasternack, Dan Roth
Added 15 May 2011
Updated 15 May 2011
Type Journal
Year 2011
Where WWW
Authors Jeff Pasternack, Dan Roth
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