知识重组。一种有效推理的规则模型方案

G. Biswas, G. Lee
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引用次数: 3

摘要

讨论了概念聚类在大型知识库重构中的应用,以提高知识库解决复杂问题的效率。PLAYMAKER是一个描述油气油田和油气藏特征的系统,它的规则库使用我们的概念聚类方案ITERATE重组为规则模型的层次结构。与特定于任务的推理方法一起使用的规则模型提供了更有效、更集中和更健壮的推理机制。一组已经进行的案例研究证明了推理系统性能的改进。PLAYMAKER是在mid(混合推理Dempster-Shafer工具)上实现的,这是一个通用的基于知识的系统构建工具,它结合了基于任务特定架构和信念函数的推理机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Knowledge reorganization. A rule model scheme for efficient reasoning
Discusses the application of conceptual clustering in restructuring large knowledge bases for the purpose of improving their complex problem solving efficiency. The rule base of PLAYMAKER, a system for characterizing hydrocarbon fields and plays, is restructured into a hierarchy of rule models using our conceptual clustering scheme, ITERATE. The rule models, used with a task-specific reasoning methodology, provide a more efficient, focused, and robust inferencing mechanism. A set of case studies that have been conducted demonstrate the improved performance of the reasoning system. PLAYMAKER is implemented on MIDST (Mixed Inferencing Dempster-Shafer Tool), a general-purpose knowledge-based system construction tool that incorporates reasoning mechanisms based on a task-specific architecture and belief functions.<>
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