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dc.contributor.authorMain, J.
dc.contributor.authorDillon, Tharam S.
dc.contributor.authorWitten, M.
dc.date.accessioned2017-01-30T12:19:30Z
dc.date.available2017-01-30T12:19:30Z
dc.date.created2008-11-12T23:36:26Z
dc.date.issued2007
dc.identifier.citationMain, Julie and Dillon, Tharam S. and Witten, Mary. 2007. Adaptation Knowledge from the Case Base, in Orgun, Mehmet A. and Thornton, John (ed), AI 2007: Advances in Artificial Intelligence, pp 579-588. Heidelberg: Springer-Verlag.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/20481
dc.identifier.doi10.1007/978-3-540-76928-6_59
dc.description.abstract

Case adaptation continues to be one of the more difficult aspects of case-based reasoning to automate. This paper looks at several techniques for utilising the implicit knowledge contained in a case base for case adaptation in case-based reasoning systems. The most significant of the techniques proposed are a moderately successful data mining technique and a highly successful artificial neural network technique. Their effectiveness was evaluated on a footwear design problem.

dc.publisherSpringer-Verlag
dc.titleAdaptation Knowledge from the Case Base
dc.typeBook Chapter
dcterms.source.startPage579
dcterms.source.endPage588
dcterms.source.titleAI 2007: Advances in Artificial Intelligence
dcterms.source.placeHeidelberg
dcterms.source.chapter101
curtin.note

The original publication is available at https://link.springer.com/

curtin.departmentCentre for Extended Enterprises and Business Intelligence
curtin.identifierEPR-2891
curtin.accessStatusOpen access
curtin.facultyCurtin Business School


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