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1、ProceedingsoftheNinthInternationalConferenceonMachineLearningandCybernetics,Qingdao,11-14July2010DATAMININGPROCESSMODELFORMARKETINGANDCRMDINGPANCenterforBusinessIntelligenceResearch,SchoolofManagement,JinanUniversity,Guangzhou510632,ChinaE-MAIL:tpandingcn@jnu.edu.cnAbstract:thatres
2、ultedfrominteractionsbetweenresearchersandTheroleofdatamininghasbecomeincreasinglyimportantindustrialdataanalysts[2].ThemodeldidnotaddressfororganizationalmarketingthathaslargedatabasesofparticularDMtechniques,butratherprovidedsupportfortheinformationoncustomers.Thedataminingresear
3、chershavecomplicatedandhighlyiterativeprocessofknowledgepresentedvariousminingalgorithmstoextractpatternsindatageneration.Sincethen,severaldifferentprocessmodelshaveforsuccessfulCRMapproach.ThetraditionaldominantKDDbeendeveloped.Theseprocessmodelsconsistofmultipleprocessmodeloffers
4、valuableguidanceonthestepsexecutedinasequence,whichoftenincludesloopsandprojected-managementorientedstages,withnorelevantmechanismtoprovideguidanceinthecrucialissueofbusinessiterations.Eachsubsequentstepisinitiatedupontheunderstanding,modelselectionandknownknowledgesuccessfulcomple
5、tionofapreviousstep,andrequiresaresultintegration.Therequirementsofcontinuousdatamininggeneratedbythepreviousstepasitsinputs[3-6].processformarketingandCRMenvironmentaredescribed,TheCRISP-DM(CRossIndustryStandardProcessforandthenanovelintegrativeframeworkforknowledgediscoveryDataMi
6、ning)processmodelincludessixsteps:businessprocessisproposed,andaknowledgeconceptualhierarchytounderstanding,dataunderstanding,datapreparation,characterizetheprocessoperationfeaturesandinterrelationsismodeling,evaluationanddeployment[5].TheCRISP-DMdiscussed.modelseemstohavebecomethe
7、dominant,butoneofmainlimitationsisthatitisessentiallysequentialandlinear.EvenKeywords:thoughfeedbackloopsarementioned,thesequentialnatureProcessmodel;Campaignmanagement;Knowledgeoftherepresentationsuggestsanorderingoftheknowledgemanagementspace,anditsexploration,whichdoesnotappropr
8、iatelycharacterizethehiera
