Data Mining with Distributed Agents in E-Commerce Applications

Y. Lee, University of Missouri, USA; J. Geller, New Jersey Institute of Technology, USA; E. K. Park and C. Oh, University of Missouri, USA

In this paper we describe the prototype of a yellow page service for customers in a distributed cyber-shopping mall. This application combines distributed data mining with agent technologies. The paper focuses on a framework to support distributed data mining. Data mining approaches have dealt with finding interesting patterns, however, there is little research on developing a framework for effective and efficient distributed data mining. Our approach to providing such a framework combines a concept hierarchy and an efficient, distributed encoding of that concept hierarchy with existing data mining methods. This marriage results in a new distributed data representation for data mining, called Combined Hierarchical Set (CHS). CHS provides a framework for knowledge discovery including discovery of generalized associations, aggregated associations, and combined associations.

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