欢迎来到天天文库
浏览记录
ID:32199065
大小:1.92 MB
页数:98页
时间:2019-02-01
《数据挖掘技术在预防电信客户流失中的应用分析》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、\●浙江1:业人学硕+学位论文THERESEARCHoNAPPLYINGDATAMININGToPREVENTINGTHELoSSoFCUSToMERSABSTRACTIIlCllina’since2008seVeraltelecomoperatl3rShadbeenconsolidated.AsⅡleIooseningofmetelecommuIlications访dus仃ycontrol锄dnewtechnologiesapplied,tlle、ⅣirelesstelecommuIlicatio璐marketis鼢turated锄dfierCeCo
2、mpetitionisincre嬲ing.Theref.0re,tllecuStomerch啪prediction锄dm锄agementa陀evenmo陀impon锄tt0telccomserviCeproVide瑙.Insuchasatur纳edtelecommark吒meywillw眦tomeet也eneedsofcustomers锄dretaillcustomerS.Therefore,tlleyhopetllatuSingtcc腼calmemodc髓predictthepossiblech啪erS,tllentelcCom∞rviccpr0Vi
3、derStakcata:曙ctcds眦cgyt0tllcSccustome塔锄danendt0陀taintllem.However’p川ictingt11epossiblech啪e璐isdifficult’觚dmedissertationu∞da_tamining眦hIlologyt0buildap川ictiVemodel,findouttllepossiblech哪e瑙锄dpr0VidepersonalizedseⅣice.Them2Lintasksoftlledisserlationarelistedasbelow:1.Compa陀di艉rentd
4、a_tamimngtoolsuSedcun℃ntly锄ddescribet}leiradV锄tages觚ddisadVantages;in臼oduCetllecurrentresearchofcuStomerch啪management.2.EstablishrelatiVelyhi曲predictionper:fonn锄cech啪锄aIysismodelbaSedontIledecisionn℃e锄dneuralne铆ork.Givea‰eworkofcus幻merCh啪锄alysissystem,觚dpropose锄alyticaJproccdure
5、,minemwdat‰tIlengiVetIleprocessofpredictiVemodel.3.EVm岫钯tllesemodelsuSingempiric2Lldata.Explo陀dataanalysis,thenextractt11eda饥cIustercuStomer,tcstmodels,veri匆itse髋ctiveness锄dsklbili何EVaJ似ionresultSshowthatusingiⅢ.0砷ationofcustome璐,con心act'servicestat吣,caJldetails锄dcuStomerservice
6、陀latedda慨tllemodelc锄efl’e“VelyachieVeaCcurateprediCtiondata.Asfortllechoiceofdia’erentda协miningtecⅢques,wefindtllatmedecision骶eorneuraJneMorkapplicatio舾c锄achieVegoodprediction∞cumCy.KeyWords:CustomerCh啪M锄agement'Prediction,DataMining,Decision1’rce,NeurmNe“旧rklIt浙江:’r=业人学硕+学位论文摘要
7、⋯⋯⋯⋯⋯⋯。第l章绪论⋯。目录⋯⋯..I-1-1.1研究背景⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯..1.1.2研究意义⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯.2.1.3研究目标⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯..3.1.4研究流程⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯.3.1.5本文主要研究内容和工作⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯.4.第2章客户流失管理和数据挖掘技术.5.2.1客户流失管理⋯⋯⋯⋯⋯⋯⋯
8、⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯...5.2.1.1客户流火定义⋯⋯⋯⋯⋯⋯⋯
此文档下载收益归作者所有