by Dianshuang Wu, Jie Lu, Guangquan Zhang
Abstract:
Many business situations such as events, products and services, are often described in a hierarchical structure. When we use case-based reasoning (CBR) techniques to support business decision-making, we require a hierarchical-CBR technique which can effectively compare and measure similarity between two hierarchical cases. This study first defines hierarchical case trees (HC-trees) and discusses related features. It then develops a similarity evaluation model which takes into account all the information on nodes’ structures, concepts, weights, and values in order to comprehensively compare two hierarchical case trees. A similarity measure algorithm is proposed which includes a node concept correspondence degree computation algorithm and a maximum correspondence tree mapping construction algorithm, for HC-trees. We provide two illustrative examples to demonstrate the effectiveness of the proposed hierarchical case similarity evaluation model and algorithms, and possible applications in CBR systems.
Reference:
Similarity measure models and algorithms for hierarchical cases (Dianshuang Wu, Jie Lu, Guangquan Zhang), In Expert Systems with Applications, Elsevier Ltd, 2011.
Bibtex Entry:
@article{Wu2011,
abstract = {Many business situations such as events, products and services, are often described in a hierarchical structure. When we use case-based reasoning (CBR) techniques to support business decision-making, we require a hierarchical-CBR technique which can effectively compare and measure similarity between two hierarchical cases. This study first defines hierarchical case trees (HC-trees) and discusses related features. It then develops a similarity evaluation model which takes into account all the information on nodes’ structures, concepts, weights, and values in order to comprehensively compare two hierarchical case trees. A similarity measure algorithm is proposed which includes a node concept correspondence degree computation algorithm and a maximum correspondence tree mapping construction algorithm, for HC-trees. We provide two illustrative examples to demonstrate the effectiveness of the proposed hierarchical case similarity evaluation model and algorithms, and possible applications in CBR systems.},
author = {Wu, Dianshuang and Lu, Jie and Zhang, Guangquan},
doi = {10.1016/j.eswa.2011.05.040},
issn = {09574174},
journal = {Expert Systems with Applications},
keywords = {Case-based reasoning,Hierarchical cases,Hierarchical similarity,SML-LIB-BIBLIO,Tree similarity measuring,lang:ENG},
mendeley-tags = {SML-LIB-BIBLIO,lang:ENG},
month = jun,
publisher = {Elsevier Ltd},
title = {{Similarity measure models and algorithms for hierarchical cases}},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0957417411008244},
year = {2011}
}