An Integrated Classification Rule Management System for Data Mining

Abstract

Classification rule mining plays significant roles in practical applications. While how to mine classification rules from a database efficiently is an important issue, how to manage and apply the mined rules effectively is the same important. This paper presents a classification rule mining management system, named SM-Classifier, which integrates the functionality of generation, querying, maintenance and application of classification rules. The architecture of SM-Classifier, the classification algorithm, the rule store structure, and the rule query operations are described.

This work is partially supported by the Foundation for University Key Teacher, the Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institutions, and the Cross Century Excellent Young Teacher Foundation of the Ministry of Education of China.