基于有向项集图的关联规则挖掘算法研究与应用

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1、天津大学博士学位论文基于有向项集图的关联规则挖掘算法研究与应用姓名：温磊申请学位级别：博士专业：管理科学与工程指导教师：李敏强20031201AbstractDalaminingwhichisalsoreferredasknowledgediscoveryindatabases，meansaprocessoffindingnontrivial，extractionofimplicit，perviousunknownandpotentialusefulinformationfromdataindatabase．Associationrulesmi

2、ningasailimportantfieldofdataminingdiscoverinterestingrelationshipsamongattributesinthosedata．Byreadingtheliteraturedomesticandabroad，Weresearchsomeproblemofassociationrulesminingalgorithms，themaincontextsandinnovationsareshowedasfoilow：1．Wediscusstherelationshipbetweenlatti

3、cetheory,formalconceptanalysisandassociationrulesminingandintroducaseriesofdefinitionandpropertyofassociationrulesmining．2，AnewfrequentitemselminingalgorithmsbasedDDDirectedJlemsetGraph(DISG)isintroduced．BystoringinformationoffrequentitemsetinDISG．Theproblemofdiscoveringthef

4、requentitemsetfromdatabaseistransformedintothesearchproblemofDISG．3．AnewmaximalfrequentitemsetminingalgorithmsbasedonDISGisintroducedtodiscoverthelongfrequentpattern．Byusingdepth-firststrategy,thealgorithmsprunethesearchingspacebycomputingthefrequentextensionsetofitemsetandd

5、iscoverallthemaximaJfrequentitemselefficiently．4．AnewalgorithmsofminingfrequentcloseditemselbasedonDISGisinlxoduced．Byusingdepth-firststrategythealgorithmsprunethesearchingspacebyjudgingthepropertyof台equeⅡtctosedseedsetanddiscoverallthefrequerttctoseitemselefficiently．5．Them

6、iningalgorithmsofincrementalupdatefrequentitemset，incrementalupdatemaximalfrequentitemsetandincrementalupdatefrequentcloseditemsetaredesignedbasedonDISG,．Thesealgorithmsc肋efficientlyutilizetheresu]lminedanddiscovertheupdatedfrequentitemsetefficiently．Thealgorithmsproposedint

7、hispaperistestedbyusingthelargescaledenseda'．asetwhicha11showgoodperformances．Wemakeanappticat{oneX嘲,'；IAep．t．撕血thedatasetofpowerstationandachievesomevaluableinformation．Keyword：DataMioing，Directed[temsetGraph，AssociationRule，FrequentRemset，MaximalFrequentltemset．FrequentClo

8、sed]temset，IncrementalUpdateMining独创性声明本人声明所呈交的学位论文是本人在导师指导下进行的研究工作和取得的研究成果