基于TF-IDF的通用案例推理方法研究

Lin Zhang
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引用次数: 2

摘要

随着案例推理(Case-Based Reasoning, CBR)技术应用领域的不断扩大,程序员获取和表达专业知识的难度越来越大。因此,对基于案例推理的通用案例检索模型的需求日益增长。本文首先对专业知识进行结构化表达,并将基于案例的推理方法与关键字权重的科学度量(Term Frequency- inverse Document Frequency, TF-IDF)相结合,设计了案例推理技术中的案例组织、案例检索和案例保留。它为一般案例检索模型提供了一种有效的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Research on General Case-Based Reasoning Method Based on TF-IDF
With the continuous expansion of the application field of Case-Based Reasoning (CBR) technology, it is increasingly difficult for programmers to acquire and express professional knowledge. Therefore, the demand for general case retrieval model based on Case-Based Reasoning is rising. This paper first gives a structured expression of professional knowledge, and combines the Case-Based Reasoning method with the scientific measurement of keyword weight (Term Frequency-Inverse Document Frequency, TF-IDF) to design the case organization, case retrieval and case retaining in CBR technology. It provides an effective method for general case retrieval model.
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