Synthesizing global association rules in multi database mining

dc.contributor.guideSrinivasan Ren_US
dc.coverage.spatialSynthesizing global association rules in multi database miningen_US
dc.creator.researcherRamkumar Ten_US
dc.date.accessioned2014-12-17T05:34:37Z
dc.date.available2014-12-17T05:34:37Z
dc.date.awarded30/05/2010en_US
dc.date.completed01/05/2010en_US
dc.date.issued2014-12-17
dc.date.registeredn.d.en_US
dc.description.abstractAdvances in information and communication technologies demand newlinevarious new perceptions in industrial growth and business activities In newlinepractice the required data for corporate decisions are spread over multiple newlinebranches which are physically located in different regions In such situations newlinetraditional data mining techniques based on data warehousing have serious newlinelimitations like high investment on software hardware and difficulties in newlinefinding the individuality of local patterns apart from the necessity of moving newlinehuge quantity of data to the central data warehouse The problem could be newlineovercome by using MultiDatabase mining based on local pattern analysis newlinePatterns can be discovered using various data mining functionalities in which newlineassociation analysis receives significant attention in the KDD community newline newlineen_US
dc.description.noteReference p.144-151en_US
dc.format.accompanyingmaterialNoneen_US
dc.format.dimensions23cmen_US
dc.format.extentxx, 153p.en_US
dc.identifier.urihttp://hdl.handle.net/10603/30952
dc.languageEnglishen_US
dc.publisher.institutionFaculty of Science and Humanitiesen_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.relationp.144-151en_US
dc.rightsuniversityen_US
dc.source.universityUniversityen_US
dc.subject.keywordmulti databaseen_US
dc.subject.keywordscience and humanitiesen_US
dc.subject.keywordSynthesizingen_US
dc.titleSynthesizing global association rules in multi database miningen_US
dc.title.alternativeen_US
dc.type.degreePh.D.en_US

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