数据仓库和数据挖掘技术在民航快递中的应用

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1、?《瓣：Ⅻ粼I耵囊积黪目增。警释缴糕蠢耋硕士学位论文论文题目数据仓库和数播挖掘技术在民航快递中的应用作者姓名段军晓学科专业计算机科学与技术导师姓名石履超完成时间2005年1O月中国科·、≯技术大学硕十学位论文数据仓库和数据挖掘技术在民航快递中的应州AbstractSameasmanyotherdomesticcompanies，ChinaAirExpressCo，，Ltd(CAE)hasconductedinformationizationworkformanyyears，andhasaccumulat

2、edsomedatainthedatabases．However,thedatabasesisclassifiedtodifferentpartsandisusedintemallybydifferentdepartments．Meanwhile，thedifferentstandardadoptedinissuingstatisticresultsinconflictandcontradictionamongtheconclusions．Besides，beforesomuchmultifarious

3、data，CAEcannotfindthevaluableinformationtosupportcompany'sdecisionmaking．DataWarehouseandDataminingtechnologyisjustindicatingthedirectionofsolvingtheseproblems，Inthisarticle，theauthorintroducesDatabasesWarehouseandDataminingtechnology,meanwhile，makesadee

4、presearchonCAE’spractice；combiningwhichwithDataWarehouseandDataminingtheory,theauthorproposesthesolutiontoCAEdatabases．Onthatbase，theauthorexplorestheminingassociationrules，findingtheoptimizedrulesandappliesittoCAE’sDataWarehousing．Thecontributionofthisa

5、rticleissummarizedhere：Inthefirstchapter,theauthorintroducesthebackgroundoftheresearch，theconceptandrelationofDataWarehouseandDatamining．Andalso，theauthordescribeshisdetailedwork．．Inthesecondchapter,theauthordetailedexpoundstheconceptanddevelopmentofData

6、bases，andanalyzesthestructureandapplicationofdatabasesaccordingtoCAE’spracticalcondition．Inaddition，theauthorrealizestheestablishmentofdatamodelbasedontheapplication．Inthethirdchapter,theauthorintroducestheconceptmaddevelopmentofOLAP,therelationbetweenOL

7、APandOLTP,andtheapplicationofOLAPincompany’srelationdatabase．intheforthchapter,theauthorintroducestheminingassociationrules，particularlyintheprocedureofApriorirules，furthermore，appliestheoptimizedrulesintheCAE’srelationdatabases．hlthefifthchapter,theauth

8、orintroducestheimplementconfigureofCAElsdistributed．¨】．窖98i：!}中国科学技术人学硕士学位论文数据仓库和数据挖掘技术在民航快递中的应用DataWarehouse，thefrontimplementofitsB／SmodelandthestructureofDimensionandCuberealizedbyOracle9iDataWarehousetools．KeywordsData