TCBR中案例相关度及案例冗余处理模型  

The Similarity Measure and Redundancy Solution of Case in Textual CBR

作　　者：杨健[1] 张晓玲[1] 周少云[1] 

机构地区：[1]大理学院数学与计算机学院,云南大理671003

出　　处：《电脑知识与技术》2006年第6期188-189,203,共3页Computer Knowledge and Technology

摘　　要：首先介绍基于文档的案例推理技术TCBR,以及CRN、IEs等基本理论,然后详细介绍CRN的构建过程和相关的函数模型,并提出一个求和函数来计算案例与当前问题的相关值,在文章的后面阐述了TCBR的案例学习方法以及案例相似程度的一个判断函数,并提出在这种情况下对案例冗余的处理方案。At first,we describe the Principle of Textual Case-based Reasoning, Case Retrieval Nets,Information Entities. Then we put forward to a new sum function to compute the similarity between cases and the problem. At the end of the Article, we present a case-learning measure and a judge function of the similarity measure in TCBR, and we put forward to a method for redundancy solution of case In this case.

关 键 词：Case-based Reasoning(CBR) TEXTUAL CBR(TCBR) Case RETRIEVAL Nets(CRN) Information Entities(IEs) 实例学习 实例冗余处理 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]