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An algorithm for knowledge integration and refinement

Ping Guo, Fan Li, Lian Ye, Jianqiu Cao

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Abstract

Knowledge base is the foundation of intelligent system. It is very important to insure the consistency and non-redundancy of knowledge in knowledge base. The redundant, inclusive and incompatible knowledge must be processed in knowledge-integration due to variety of knowledge source. In this paper, we research the incompatible knowledge elimination approach in knowledge-integration based on rough set theory, and present a new knowledge integration algorithm KIRRS, which is effective to improve the efficiency of knowledge-integration.

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What this paper is about

Knowledge base is the foundation of intelligent system. It is very important to insure the consistency and non-redundancy of knowledge in knowledge base. The redundant, inclusive and incompatible knowledge must be processed in knowledge-integration due to variety of knowledge source. In this paper, we research the incompatible knowledge elimination approach in knowledge-integration based on rough set theory, and present a new knowledge integration algorithm KIRRS, which is effective to improve the efficiency of knowledge-integration.

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Available abstract

Knowledge base is the foundation of intelligent system. It is very important to insure the consistency and non-redundancy of knowledge in knowledge base. The redundant, inclusive and incompatible knowledge must be processed in knowledge-integration due to variety of knowledge source. In this paper, we research the incompatible knowledge elimination approach in knowledge-integration based on rough set theory, and present a new knowledge integration algorithm KIRRS, which is effective to improve the efficiency of knowledge-integration.

Key concepts: Knowledge base, Knowledge integration, Computer science, Knowledge-based systems, Redundancy (engineering), Consistency (knowledge bases), Knowledge engineering, Open Knowledge Base Connectivity

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