Integrating Multiple Knowledge Sources by Genetic Programming

Abstract

In this paper, we have proposed a GP-based knowledge-integration framework that automatically combines multiple rule sets into one integrated knowledge base. The proposed framework consists of three phases: knowledge collection and translation, knowledge integration, and knowledge output. Two new genetic operators, abridgement and compromise, are designed in the proposed approach. Experimental results from diagnosis of breast cancer also show the feasibility of the proposed algorithm.