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A living expert system needs a mechanism to update and increase knowledge to adapt this changeable world and the knowledge acquired by different approaches need storage in order for reasoning and updating conveniently. The method presented in this paper bears this mission. Simulating the learning procedure of human beings is the core idea of this method from which we can find the ways how to add, delete, amend and use the knowledge in an expert system. Based on the analysis of the common procedure of children's actions during recognizing the world, a cognitive model of concept learning is abstracted. A general concept learning algorithm, a knowledge representation method based on general rules, a logical structure in the forest shape, and a uniform data structure for storage are accordingly presented. Thus, a complete and more scientific management case for the knowledge base of expert system is provided. At last, comparing with some ontology knowledge bases, such as CYC, Word Net, and NKI, two different characteristics of this management method are discussed.