基于概念格模型关联规则挖掘的关键问题研究

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1、分类号I巳!璺UDC——密级YJ054490单位代码!Q§艘学号Q≥圣!Q墨垒§Q!QQ圣皇夺肥工学火警博士学位论文王德兴指导教师姓名刘晓平教授胡学钢教授合肥工业大学计算机与信息学院申请学位级别博士专业名称计算机应用技术提交论文日期2006年11月论文答辩日期2007年1月11日学位授予单位和日期合肥工业大学答辩委员会主席评阅人张铃教授张铃教授熊焰教授2006年11月AbstractAssociationroleminingisanimportantbranchofdatamining，theresearchandapplicationsonwhichhavebeenalready

2、madesignificantprogress．However，duetotheimmensedata，heterostructureandmultiplicityofdatatypes，complicateddatastructuresindatabasesareavailableintherealworld，thosehavemadeassociationruleminingfacealotofchallenges，therefore，thecompleteconceptlatticemodelisintroducedtothestudyofassociationmlemini

3、nginthedissertation，andsomestudiesalgmadeonconceptlatticemodel，algorithms，anddatareductionetc．Contributionsofthedissertationareasfollows：1．Onthebasisofstudyontherelationshipofconceptlatticemodelandfrequentitemsets，theitemsetsrepresentationandtheirsolutionmethodsareproposed．Thestudyshowsthateac

4、hitemsetshouldbepresentedastheintentsorsub-intentsofoneconceptintheconceptlattice，thusitisabletocompletelydescribetheseitemsets，similarly,manyitemsetsarederivedfromoneconceptthroughtherelationsamongconceptsintheconceptlattice，consequently'thenumberofconceptsintheconceptlatticeisreducedmoremark

5、edlythanthatofitemsetsintransactiondatabases，whichcarlbeusedinKDDeffectivelywithoutanyvalidinformationloss，Besides，prunedconceptlattice，derivedformconceptlatticebydeletingtheinfrequentconcepts，notonlycutsefficientlydownthesizesofdatabases，butalsoisconvenienttoassociationrulemining．2．Thestudyis

6、madeonthesolutiontoassociationruleminingalgorithmbasedontheprunedconceptlattice，thebuildalgorithmsofsequentialandsynchronalprunedconceptlatticeisproposed，theformerconstructsconceptlatticebytherecordsinsertiononthebasisofGodinbuildalgorithm，whichneedscanthedatabasesonlyonce，finishesthepruningby

7、theAprioripropertiesafterhavingcompletedtheconceptlatticeconstruction，whereas，thelatterdynamicallyconstructsconceptlatticebytheattributesinsertion，whichimplementsthepruningbytheAprioripropertiesinthecourseofconceptlatticeconstruction，th