Abstract
Data mining slowly evolves from simple discovery of frequent patterns and regularities in large data sets toward interactive, user-oriented, on-demand decision supporting. Since data to be mined is usually located in a database, there is a promising idea of integrating data mining methods into database management systems (DBMS). In this paper we present the results of developing our research prototype for DBMS-integrated data mining. We focus on two main contributions: query language for data mining and constraints-driven algorithm for association rules discovery.
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