]> 2012-05-28T01:02:33-04:00 Explaining results from information retrieval and integration Information retrieval and integration systems typically must handle incomplete and inconsistent data. Current approaches attempt to reconcile discrepant information by leveraging data quality, user preferences, or source provenance information. Such approaches may overlook the fact that information is interpreted relative to its context. Therefore, discrepancies may be explained and thereby resolved if contexts are taking into account. In this paper, we describe an information integrator that is capable of explaining its results. We focus on using knowledge of an assumption context learned through decision tree-based classification to inform the explanations. We further discuss some benefits and difficulties of applying assumption context in information retrieval. Finally, we indicate how to use Inference Web to explain discrepancies resulting from information retrieval and integration applications. inproceedings International Symposium on Explanation-aware Computing, AAAI Symposium KSL-05-08 Explaining Results from Information Retrieval and Integration KSL-05-08 2005 Year Tr id Title Computer science Tag Paper url Media:KSL-05-08.pdf Paper Extended Abstract. Note November Month Key Booktitle Bibtype Richard Fikes Paulo Pinheiro da Silva Deborah L. McGuinness Honglei Zeng Author Washington, D.C. Address Abstract KSL Technical Report Publication Proceeding Paper Workshop Paper