Refinement of the structure of knowledge base by learning

Abstract

It is argued that some failure in the existing expert systems mainly results from the ill-organized knowledge bases. The authors propose an effective structure for a knowledge base called a solution-oriented structure, which is different from various existing knowledge base structures. Using several strategies of machine learning, an expert system tool called THOUGHT can reorganize the systematic structure into a solution-oriented structure. On the basis of the solution-oriented structure, THOUGHT can perform the three-level inference for solving different kinds of problems. The solution-oriented structure of the knowledge base is efficient and effective on large, complicated knowledge bases and time critical situations.<>