Framework of a Multi-agent KDD System

  • Authors:
  • Ning Zhong;Yasuaki Matsui;Tomohiro Okuno;Chunnian Liu

  • Affiliations:
  • -;-;-;-

  • Venue:
  • IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
  • Year:
  • 2002

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Abstract

How to increase both autonomy and versatility of a knowledge discovery system is a core problem and a crucial aspect of KDD (Knowledge Discovery and Data Mining). We have been developing a multi-agent based KDD methodology/system called GLS (Global Learning Scheme) for performing multi-aspect intelligent data analysis as well as multi-level conceptual abstraction and learning. With multi-level and multi-phase process, GLS increases versatility and autonomy. This paper presents our recent development on the GLS methodology/system.