通过学习优化知识库结构

Chengjiang Mao, J. Hong
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引用次数: 1

摘要

认为现有专家系统的一些故障主要是由于知识库组织不良造成的。作者提出了一种有效的知识库结构,即面向解决方案的知识库结构,它不同于现有的各种知识库结构。使用几种机器学习策略,一个名为THOUGHT的专家系统工具可以将系统结构重组为面向解决方案的结构。在面向解决方案的结构基础上,思想可以对不同类型的问题进行三层推理。面向解决方案的知识库结构在大型、复杂的知识库和时间紧迫的情况下是高效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Refinement of the structure of knowledge base by learning
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.<>
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