The Design of an Intelligent Case Library Construction for Case-Based Reasoning
碩士 === 輔仁大學 === 資訊工程學系 === 93 === Successful case-based reasoning systems heavily depend on the completeness of the case library. It is difficult to extract the cases and find the solution from the haphazard case library. It may increase the adaptation cost from the sparse case library with few ca...
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ndltd-TW-093FJU003920272015-12-23T04:08:14Z http://ndltd.ncl.edu.tw/handle/89156334350362917388 The Design of an Intelligent Case Library Construction for Case-Based Reasoning 案例式推理智慧型案例庫建構系統之設計 Yu-Gin Tian 田育君 碩士 輔仁大學 資訊工程學系 93 Successful case-based reasoning systems heavily depend on the completeness of the case library. It is difficult to extract the cases and find the solution from the haphazard case library. It may increase the adaptation cost from the sparse case library with few cases. This paper proposes an intelligent case library construction system for case-based reasoning. The system contains two modules, that is, data analyzer and case extractor. The data analyzer fills missing feature value and deletes irrelevant features according to the frequency, dependency, and importance of features. The data analyzer then project the feature value into two-dimensional feature space to conduct data reduction and data evaluations. The case extractor groups the data of feature space into different clusters according to the coordination in the geometrical space and data covariance. Finally, the case extractor takes the center of each cluster as representative case based on the distance, frequency, and value difference evaluation. The system provides a systematic approach to do data reduction as well as complete case-library construction process. It not only extracts the representative case from the database but also improve the efficiency of case-based reasoning by setting the initial weights of each feature. Chien-Chang Hsu 許見章 2005 學位論文 ; thesis 64 zh-TW |
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碩士 === 輔仁大學 === 資訊工程學系 === 93 === Successful case-based reasoning systems heavily depend on the completeness of the case library. It is difficult to extract the cases and find the solution from the haphazard case library. It may increase the adaptation cost from the sparse case library with few cases. This paper proposes an intelligent case library construction system for case-based reasoning. The system contains two modules, that is, data analyzer and case extractor. The data analyzer fills missing feature value and deletes irrelevant features according to the frequency, dependency, and importance of features. The data analyzer then project the feature value into two-dimensional feature space to conduct data reduction and data evaluations. The case extractor groups the data of feature space into different clusters according to the coordination in the geometrical space and data covariance. Finally, the case extractor takes the center of each cluster as representative case based on the distance, frequency, and value difference evaluation. The system provides a systematic approach to do data reduction as well as complete case-library construction process. It not only extracts the representative case from the database but also improve the efficiency of case-based reasoning by setting the initial weights of each feature.
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author2 |
Chien-Chang Hsu |
author_facet |
Chien-Chang Hsu Yu-Gin Tian 田育君 |
author |
Yu-Gin Tian 田育君 |
spellingShingle |
Yu-Gin Tian 田育君 The Design of an Intelligent Case Library Construction for Case-Based Reasoning |
author_sort |
Yu-Gin Tian |
title |
The Design of an Intelligent Case Library Construction for Case-Based Reasoning |
title_short |
The Design of an Intelligent Case Library Construction for Case-Based Reasoning |
title_full |
The Design of an Intelligent Case Library Construction for Case-Based Reasoning |
title_fullStr |
The Design of an Intelligent Case Library Construction for Case-Based Reasoning |
title_full_unstemmed |
The Design of an Intelligent Case Library Construction for Case-Based Reasoning |
title_sort |
design of an intelligent case library construction for case-based reasoning |
publishDate |
2005 |
url |
http://ndltd.ncl.edu.tw/handle/89156334350362917388 |
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