Knowledge discovery in biomedical data facilitated by domain ontologies

Sidhu, AS; Kennedy, PJ; Simoff, S; Dillon, TS; Chang, E

Knowledge discovery in biomedical data facilitated by domain ontologies

Sidhu, AS Kennedy, PJ

Simoff, S Dillon, TS Chang, E

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Publication Type:: Chapter
Citation:: Knowledge Discovery and Data Mining: Challenges and Realities, 2007, pp. 189 - 201
Issue Date:: 2007-12-01

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Field	Value	Language
dc.contributor.author	Sidhu, AS	en_US
dc.contributor.author	Kennedy, PJ https://orcid.org/0000-0001-7837-3171	en_US
dc.contributor.author	Simoff, S	en_US
dc.contributor.author	Dillon, TS	en_US
dc.contributor.author	Chang, E	en_US
dc.date.issued	2007-12-01	en_US
dc.identifier.citation	Knowledge Discovery and Data Mining: Challenges and Realities, 2007, pp. 189 - 201	en_US
dc.identifier.isbn	9781599042527	en_US
dc.identifier.uri	http://hdl.handle.net/10453/7858
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 knowledge into the pattern recognition task for biomedical data. © 2007, IGI Global.	en_US
dc.relation.ispartof	Knowledge Discovery and Data Mining: Challenges and Realities	en_US
dc.relation.isbasedon	10.4018/978-1-59904-252-7.ch010	en_US
dc.title	Knowledge discovery in biomedical data facilitated by domain ontologies	en_US
dc.type	Chapter
utslib.for	080301 Bioinformatics Software	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

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 knowledge into the pattern recognition task for biomedical data. © 2007, IGI Global.

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http://hdl.handle.net/10453/7858