Novel applications of Association Rule Mining- Data Stream Mining

aut.embargoNoen
aut.thirdpc.containsNo
aut.thirdpc.permissionNo
aut.thirdpc.removedNo
dc.contributor.advisorPears, Russel
dc.contributor.authorVithal Kadam, Omkar
dc.date.accessioned2010-03-12T01:29:08Z
dc.date.available2010-03-12T01:29:08Z
dc.date.copyright2009
dc.date.issued2009
dc.date.updated2010-03-12T01:17:16Z
dc.description.abstractFrom the advent of association rule mining, it has become one of the most researched areas of data exploration schemes. In recent years, implementing association rule mining methods in extracting rules from a continuous flow of voluminous data, known as Data Stream has generated immense interest due to its emerging applications such as network-traffic analysis, sensor-network data analysis. For such typical kinds of application domains, the facility to process such enormous amount of stream data in a single pass is critical.
dc.identifier.urihttps://hdl.handle.net/10292/826
dc.language.isoenen
dc.publisherAuckland University of Technology
dc.rights.accessrightsOpenAccess
dc.subjectData stream mining
dc.subjectAssociation rule mining
dc.titleNovel applications of Association Rule Mining- Data Stream Mining
dc.typeThesis
thesis.degree.grantorAuckland University of Technology
thesis.degree.levelMasters Theses
thesis.degree.nameMaster of Computer and Information Sciences
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