Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/12335
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dc.contributor.authorDetterer, Dionen
dc.contributor.authorKwan, Paul Hen
local.source.editorEditor(s): Longbing Cao, Joshua Zhexue Huang, James Bailey, Yun Sing Koh, Jun Luoen
dc.date.accessioned2013-03-26T11:46:00Z-
dc.date.issued2012-
dc.identifier.citationNew Frontiers in Applied Data Mining, p. 361-371en
dc.identifier.isbn9783642283208en
dc.identifier.isbn9783642283192en
dc.identifier.urihttps://hdl.handle.net/1959.11/12335-
dc.description.abstractTraditional Chinese Medicine (TCM) relies heavily on interactions between herbs within prescribed formulae. However, given the combinatorial explosion due to the vast number of herbs available for treatment, the study of herb-herb interactions by pure human analysis is impractical, with computer aided analysis computationally expensive. Thus feature selection is crucial as a pre-processing step prior to herb-herb interaction analysis. In accord with this goal, a new feature selection algorithm known as a Co-evolving Memetic Wrapper (COW) is proposed: COW takes advantage of recent developments in genetic algorithms (GAs) and meme tic algorithms (MAs). evolving appropriate feature subsets for a given domain. As part of preliminary research. COW is demonstrated to he effective in selecting herbs in the TCM insomnia dataset. Finally, possible future applications of COW are examined, both within TCM research and in broader data mining contexts.en
dc.languageenen
dc.publisherSpringeren
dc.relation.ispartofNew Frontiers in Applied Data Miningen
dc.relation.ispartofseriesLecture Notes in Artificial Intelligenceen
dc.relation.isversionof1en
dc.titleCOW: A Co-evolving Memetic Wrapper for Herb-Herb Interaction Analysis in TCM Informaticsen
dc.typeBook Chapteren
dc.identifier.doi10.1007/978-3-642-28320-8_31en
dc.subject.keywordsNeural, Evolutionary and Fuzzy Computationen
dc.subject.keywordsPattern Recognition and Data Miningen
dc.subject.keywordsTraditional Chinese Medicine and Treatmentsen
local.contributor.firstnameDionen
local.contributor.firstnamePaul Hen
local.subject.for2008080109 Pattern Recognition and Data Miningen
local.subject.for2008110404 Traditional Chinese Medicine and Treatmentsen
local.subject.for2008080108 Neural, Evolutionary and Fuzzy Computationen
local.subject.seo2008920199 Clinical Health (Organs, Diseases and Abnormal Conditions) not elsewhere classifieden
local.subject.seo2008970108 Expanding Knowledge in the Information and Computing Sciencesen
local.subject.seo2008890201 Application Software Packages (excl. Computer Games)en
local.identifier.epublicationsvtls086642582en
local.profile.schoolSchool of Science and Technologyen
local.profile.emailddetter2@une.edu.auen
local.profile.emailwkwan2@une.edu.auen
local.output.categoryB1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordune-20120528-144814en
local.publisher.placeHeidelberg, Germanyen
local.identifier.totalchapters42en
local.format.startpage361en
local.format.endpage371en
local.identifier.scopusid84857715076en
local.series.issn1611-3349en
local.series.issn0302-9743en
local.series.number7104en
local.title.subtitleA Co-evolving Memetic Wrapper for Herb-Herb Interaction Analysis in TCM Informaticsen
local.contributor.lastnameDettereren
local.contributor.lastnameKwanen
dc.identifier.staffune-id:ddetter2en
dc.identifier.staffune-id:wkwan2en
local.profile.roleauthoren
local.profile.roleeditoren
local.identifier.unepublicationidune:12542en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleCOWen
local.output.categorydescriptionB1 Chapter in a Scholarly Booken
local.relation.urlhttp://trove.nla.gov.au/work/163564897en
local.search.authorDetterer, Dionen
local.search.authorKwan, Paul Hen
local.uneassociationUnknownen
local.year.published2012en
local.subject.for2020461199 Machine learning not elsewhere classifieden
local.subject.for2020420803 Traditional Chinese medicine and treatmentsen
local.subject.for2020460203 Evolutionary computationen
local.subject.seo2020280115 Expanding knowledge in the information and computing sciencesen
local.subject.seo2020220401 Application software packagesen
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