A Hypothesis Refinement Method for Summary Discovery in Databases

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dc.contributor.authorLee, Do Heon-
dc.contributor.authorKim, Myoung Ho-
dc.date.accessioned2007-11-19T05:21:45Z-
dc.date.available2007-11-19T05:21:45Z-
dc.date.issued1993-11-
dc.identifier.citationSecond Int'l Conf. on Information and Knowledge Management, Serial. 2, Washington D.C., USA, P. 274 - 292en
dc.identifier.isbn0-8979-1626-3-
dc.identifier.urihttp://doi.acm.org/10.1145/170088.170153-
dc.identifier.urihttp://hdl.handle.net/10203/2022-
dc.description.abstractAs database systems are playing major roles in more and more applications, the amount of information in databases is rapidly growing. In order to comprehend those large volumes of information, computerized summary discovery methods are required. In this paper, we propose a hypothesis refinement method for constructing and evaluating fuzzy hypotheses. Breed on them we propose an effective and robust algorithm to discover simple linguistic summaries. In addition, we present ideas for exploiting discovered summaries to various applications such as querying database knowledge, handling query failures and semantic query optimization.en
dc.description.sponsorshipInst Soc for Comp & Applic : Inst Soc for Comp & Applic SIGART: ACM Special Interest Group on Artificial Intelligence SIGIR: ACM Special Interest Group on Information Retrievalen
dc.language.isoen_USen
dc.publisherAssociation for Computing Machinery (ACM)en
dc.subjectknowledge discovery in databasesen
dc.subjectsummary discoveryen
dc.subjectfuzzy set theoryen
dc.subjectquery failureen
dc.titleA Hypothesis Refinement Method for Summary Discovery in Databasesen
dc.typeArticleen

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