基于數(shù)據(jù)挖掘的電信客戶細(xì)分模型研究.pdf

1、碩士學(xué)位論文基于數(shù)據(jù)挖掘的電信客戶細(xì)分模型研究AConsumerSegmentationModelResearchBasedonDataMininginTelecommunicationsBusiness作者姓名：學(xué)科、專業(yè)：學(xué)號(hào)：指導(dǎo)教師：完成日期：塑遣攙—暨堡型堂皇王猩一一翟≥!l壁鰻塞迢直大連理工大學(xué)Da／ianUniversityofTechnology基于數(shù)據(jù)挖掘技術(shù)的電信企業(yè)客戶細(xì)分模型研究AConsumerSegmenta

2、tionModelResearchBasedODDataMininginTelecommunicationsBUSl‘11essAbstraetOwingtointensecompetenceinintemationaltelecommunicationmarketandthedevelopmentofthemarketitselftraditionaldomesticbusinessmodelhasgraduallybecomethe

3、onebasedonconsumers，dataandinformationTherefore，consunlersegmentationistheprerequisiteandfoundationAtpresent，thecurrentsegmentationmethodissimplyallexperienceandstatisticsbasedsystem，whichdoesnotfacilitatetheinformationi

4、nterchangebetweencustomersandenterprisesAsaresultthesemethodsarefarbehindmeetingtherequirementofcomplexbusinessanalysisAlongwimthedepthspreadofdataminingamongtelecommunicationenterprisemanagementitisbecomingurgentandcrit

5、icaltoimplementmulti—level，multilatitudesandfocusedcousumersegmentationbyadoptingvariousadvanceddataminingmethods弛earticlearticulatesdataorganizationprocessingandstorageinviewoftelecommunicationenterprisesconsumersegment

6、ationduringthecourseofcustomerrelationmanagementWjmtheapplicationofdataminingtechniquespreciseande彘cdveconsumersegmentationcouldbeachievedthrou曲theemploymentoftheintroducedtheories，techaologiesandmethodsThearticleelabora

7、testheoreticallythestrate百Cimportanceontheapplicationofconsumersegmentationintelecommunicationbusinessanditsmethodsthroughintegratingcustomers’characteristicswithcustomers’li僥cycletheoryBasedontheanalysisofcurrentconsume

8、rsegmentationmethods，theauthorpointsoutthepressingneedforapplyingdataminingtechniquesinconsumersegmentationwhiledepictingadetailedpieceofhowthesegmentationfimctionsineachareaofthetelecommunicationmarketInpractice，cluster

9、analysisiSoneofthemostimportantresearchingfield，andwhilemorechallengingIthasexitedaseriesofproblemsinclusteranalysis，forexampleitisdifficulttodetectthefigureandsizeofconcentratingdata，differentdensityofcluster，sensitivit

10、ytonoisedataandSOonThisarticlehasanalyzedparticularlyandgenerallyintypicalKmeansarithmeticAccordingtothecharacteristicsoftelecomdatatheauthorpointsoutthedisadvantageandimprovingmethodsthatisdataminingmodelbasedonKmeansar

11、ithmeticappliesinconsumersegmentationsofcertainmmpanyhandyphoneshortmessagebusiness，andgetsidealconclusionthroughexaminationBasedonthisitsetsupmarketingstrategiestodifferentconsumergroup，andestablishesasteadydecisionsupp