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dc.contributor.authorSidhu, Amandeep
dc.contributor.authorKennedy, P.
dc.contributor.authorSimoff, S.
dc.contributor.authorDillon, Tharam S.
dc.contributor.authorChang, Elizabeth
dc.date.accessioned2017-01-30T15:14:48Z
dc.date.available2017-01-30T15:14:48Z
dc.date.created2008-11-12T23:36:19Z
dc.date.issued2007
dc.identifier.citationSidhu, Amandeep S. and Kennedy, Paul J. and Simoff, Simeon and Dillon, Tharam S. and Chang, Elizabeth. 2007. Knowledge discovery in biomedical data facilitated by domain ontologies. In Zhu, Xingquan and Davidson, Ian (ed), Knowledge discovery and data mining: Challenges and realities, pp 189-201. Hershey, PA, USA: IGI Global.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/44545
dc.description.abstract

In some real-world areas, it is important to enrich the data with external background knowledge so as to provide context and to facilitate pattern recognition. These areas may be described as data rich but knowledge poor. There are two challenges to incorporate this biological knowledge into the data mining cycle: (1) generating the ontologies; and (2) adapting the data mining algorithms to make use of the ontologies. This chapter presents the state-of-the-art in bringing the background ontology knowledgeinto the pattern recognition task for biomedical data.

dc.publisherIGI Global
dc.titleKnowledge discovery in biomedical data facilitated by domain ontologies
dc.typeBook Chapter
dcterms.source.startPage189
dcterms.source.endPage201
dcterms.source.titleKnowledge discovery and data mining: Challenges and realities
dcterms.source.placeHershey, PA, USA
dcterms.source.chapter13
curtin.departmentCentre for Extended Enterprises and Business Intelligence
curtin.identifierEPR-2382
curtin.accessStatusFulltext not available
curtin.facultyCurtin Business School
curtin.facultySchool of Information Systems


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