A method to eliminate incompatible knowledge and equivalence knowledge

Authors:
Ping Guo;Li Fan;Lian Ye
Affiliations:
School of Computer Science, Chongqing University, Chongqing, China;School of Computer Science, Chongqing University, Chongqing, China;School of Computer Science, Chongqing University, Chongqing, China
Venue:
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Year:
2005

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Abstract

Knowledge base is the foundation of intelligent systems. It is very important to insure the consistency and non-redundancy of knowledge in a knowledge base. Due to the variety of exterior knowledge sources, it is necessary to eliminate incompatible knowledge and equivalence knowledge in the process of knowledge integration. In this paper, we research a strategy to eliminate incompatible knowledge and equivalence knowledge in knowledge integration based on equivalence classification, and so present a new knowledge integration algorithm which is effective in improving the efficiency of knowledge integration.