Rough set approach to case-based reasoning application
The case-based reasoning becomes a novel paradigm that solves a new problem by remembering a previous similar situation and by reusing information and knowledge of that situation. In general, the traditional representation of cases is too simple and is not well structured to support the decision-mak...
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| Veröffentlicht in: | Expert systems with applications 2004-04, Vol.26 (3), p.369-385 |
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| container_end_page | 385 |
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| container_start_page | 369 |
| container_title | Expert systems with applications |
| container_volume | 26 |
| creator | Huang, Chun-Che Tseng, Tzu-Liang (Bill) |
| description | The case-based reasoning becomes a novel paradigm that solves a new problem by remembering a previous similar situation and by reusing information and knowledge of that situation. In general, the traditional representation of cases is too simple and is not well structured to support the decision-making in organization. Furthermore, the similarity testing of case-based reasoning is very time-consuming. Therefore, a novel approach to represent the knowledge of cases in an explicit manner and to search similar cases in an efficient way is desired. An Extensible Markup Language-based representation formulated with the Zachman framework is proposed in this paper. Through a rough set based approach, case-based reasoning becomes more efficient and complexity of computation of the similarity testing is significantly reduced. |
| doi_str_mv | 10.1016/j.eswa.2003.09.008 |
| format | Article |
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| fulltext | fulltext |
| identifier | ISSN: 0957-4174 |
| ispartof | Expert systems with applications, 2004-04, Vol.26 (3), p.369-385 |
| issn | 0957-4174 1873-6793 |
| language | eng |
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| source | Elsevier ScienceDirect Journals Complete |
| subjects | Case representation Case-based reasoning Knowledge management Rough set |
| title | Rough set approach to case-based reasoning application |
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