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  5. ABSTRACT-DRIVEN PATTERN DISCOVERY IN DATABASES
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dc.contributor.authorDhar, Vasant-
dc.contributor.authorTuzhilin, Alexander-
dc.date.accessioned2006-02-07T15:42:08Z-
dc.date.available2006-02-07T15:42:08Z-
dc.date.issued1992-03-
dc.identifier.urihttp://hdl.handle.net/2451/14327-
dc.description.abstractIn this paper, we study the problem of discovering interesting patterns in large volumes of data. Patterns can be expressed in user-defined terms and not only in terms of the database schema. The user-defined terminology is stored in a data dictionary that maps it into the language of the database schema. We define a pattern as a deductive rule expressed in user-defined terms that has a degree of certainty associated with it. We present methods of discovering interesting patterns based on abstracts which are summaries of the data expressed in the language of the user.en
dc.format.extent3619819 bytes-
dc.format.mimetypeapplication/pdf-
dc.languageEnglishEN
dc.language.isoen_US-
dc.publisherStern School of Business, New York Universityen
dc.relation.ispartofseriesIS-92-11-
dc.titleABSTRACT-DRIVEN PATTERN DISCOVERY IN DATABASESen
dc.typeWorking Paperen
dc.description.seriesInformation Systems Working Papers SeriesEN
Appears in Collections:IOMS: Information Systems Working Papers

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