Interactive knowledge validation and query refinement in CBR for decision support in medicine
In most case-based reasoning (CBR) systems there has been little research done on validating new knowledge, specifically on how previous knowledge differs from current knowledge as a result of conceptual change. This paper proposes two methods that enable the domain expert, who is non-expert in arti...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
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Springer
2005
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| Online Access: | http://www.aaai.org/Papers/AAAI/2005/AAAI05-036.pdf http://hdl.handle.net/20.500.11937/47870 |
| _version_ | 1848757953418493952 |
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| author | Ou, M. West, Geoff Lazarescu, Mihai Clay, C. |
| author2 | Silvia Miksch |
| author_facet | Silvia Miksch Ou, M. West, Geoff Lazarescu, Mihai Clay, C. |
| author_sort | Ou, M. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In most case-based reasoning (CBR) systems there has been little research done on validating new knowledge, specifically on how previous knowledge differs from current knowledge as a result of conceptual change. This paper proposes two methods that enable the domain expert, who is non-expert in artificial intelligence (AI), to interactively supervise the knowledge validation process in a CBR system, and to enable dynamic updating of the system, to provide the best di- agnostic questions. The first method is based on formal concept analysis which involves a graphical representation and comparison of the concepts, and a summary description high- lighting the conceptual differences. We propose a dissimilarity metric for measuring the degree of variation between the previous and current concepts when a new case is added to the knowledge base. The second method involves determining unexpected classification-based association rules to form critical questions as the knowledge base gets updated. |
| first_indexed | 2025-11-14T09:36:17Z |
| format | Conference Paper |
| id | curtin-20.500.11937-47870 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:36:17Z |
| publishDate | 2005 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-478702022-10-20T06:53:43Z Interactive knowledge validation and query refinement in CBR for decision support in medicine Ou, M. West, Geoff Lazarescu, Mihai Clay, C. Silvia Miksch Jim Hunter Selpida Keravnou In most case-based reasoning (CBR) systems there has been little research done on validating new knowledge, specifically on how previous knowledge differs from current knowledge as a result of conceptual change. This paper proposes two methods that enable the domain expert, who is non-expert in artificial intelligence (AI), to interactively supervise the knowledge validation process in a CBR system, and to enable dynamic updating of the system, to provide the best di- agnostic questions. The first method is based on formal concept analysis which involves a graphical representation and comparison of the concepts, and a summary description high- lighting the conceptual differences. We propose a dissimilarity metric for measuring the degree of variation between the previous and current concepts when a new case is added to the knowledge base. The second method involves determining unexpected classification-based association rules to form critical questions as the knowledge base gets updated. 2005 Conference Paper http://hdl.handle.net/20.500.11937/47870 http://www.aaai.org/Papers/AAAI/2005/AAAI05-036.pdf Springer restricted |
| spellingShingle | Ou, M. West, Geoff Lazarescu, Mihai Clay, C. Interactive knowledge validation and query refinement in CBR for decision support in medicine |
| title | Interactive knowledge validation and query refinement in CBR for decision support in medicine |
| title_full | Interactive knowledge validation and query refinement in CBR for decision support in medicine |
| title_fullStr | Interactive knowledge validation and query refinement in CBR for decision support in medicine |
| title_full_unstemmed | Interactive knowledge validation and query refinement in CBR for decision support in medicine |
| title_short | Interactive knowledge validation and query refinement in CBR for decision support in medicine |
| title_sort | interactive knowledge validation and query refinement in cbr for decision support in medicine |
| url | http://www.aaai.org/Papers/AAAI/2005/AAAI05-036.pdf http://hdl.handle.net/20.500.11937/47870 |