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|Title:||ABSTRACT-DRIVEN PATTERN DISCOVERY IN DATABASES|
|Publisher:||Stern School of Business, New York University|
|Abstract:||In 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.|
|Appears in Collections:||IOMS: Information Systems Working Papers|
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