摘要： CBR（Case-BasedReasoning）以完全不同于RBR（Rule—BasedReasoning）的方式在人工智能的众多技术中独树一帜。它尤其适用于难以总结出一般性规律.而又能提供大量历史事例的领域.该文着重介绍了以抽象层次法组织的，用类比法、联想检索的CBR系统：西文图书分类专家系统FCCBR*（ForeignCatalogofCase—BasedReasoningSystem）的工作机制。

关键词: 基于事例推理, 类比法, 联想检素

Abstract: CBR (Case-Based Reasoning)is one of the most distinguishing methods different from RBR(Rule-Based Reasoulng)in AI.It is applied in those fields where experiences can be provided rather than general rules. This article pays more attention to the practical CBR system with analogy method, associated retrieval: FCCBR(Foreign Catalog of Case-Based Reasoning System).

中图分类号: 

• TP391.3