ABSTRACT-DRIVEN PATTERN DISCOVERY IN DATABASES

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.