Feature Weight Maintenance in Case Bases Using introspective Learning

ZHONG ZHANG; QIANG YANG

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Feature Weight Maintenance in Case Bases Using introspective Learning

机译：使用内省式学习维护案例库中的特征权重

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A key issue in case-based reasoning is how to maintain the domain knowledge in the face of a changing environment. During the case retrieval process in case-based reasoning, feature-value pairs are used to compute the ranking scores of the cases in a case base, and different feature-value pairs may have different importance measures represented as weight values, in this computation.

机译：基于案例的推理中的关键问题是如何面对不断变化的环境来维护领域知识。在基于案例的推理中的案例检索过程中，特征值对用于计算案例库中案例的排名得分，并且在此计算中，不同的特征值对可能具有表示为权重值的不同重要性度量。

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《Journal of Intelligent Information Systems》 |2001年第2期|p.95-116|共22页
作者
ZHONG ZHANG; QIANG YANG;
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正文语种 eng
中图分类计算技术、计算机技术;
关键词
case base maintenance and indexing; knowledge base indexing; dynamic index updata through machine learning;

机译：案例库维护和索引编制;知识库索引;通过机器学习动态索引更新数据;

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Feature Weight Maintenance in Case Bases Using introspective Learning

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