基于Filter模型和随机森林的电信客户投诉分类方法-豆柴文库

您所在位置：网站首页 / 基于Filter模型和随机森林的电信客户投诉分类方法.docx / 文档详情

在线预览结束，喜欢就下载吧，查找使用更方便

5 金币

下载文档

/ 2

下载提示

如果您无法下载资料，请参考说明：

1、部分资料下载需要金币，请确保您的账户上有足够的金币

2、已购买过的文档，再次下载不重复扣费

3、资料包下载后请先用软件解压，在使用对应软件打开

文本预览

基于Filter模型和随机森林的电信客户投诉分类方法
Abstract:
Withthecontinuousimprovementofpeople'slivingstandards,thedemandfortelecommunicationsservicesisgraduallyincreasing.Thenumberofcomplaintsreceivedbytelecommunicationscompaniesisalsoincreasingyearbyyear,whichposesagreatchallengetocustomerservicemanagement.Inresponsetothischallenge,thispaperproposesaclassificationmethodfortelecommunicationscustomercomplaintsbasedontheFiltermodelandrandomforestalgorithm.Firstly,theFiltermodelisusedtopre-processandreducethedimensionalityofthedata.Then,therandomforestalgorithmisusedtoclassifythepre-processedcomplaintdataandobtaintheclassificationresults.Theexperimentshowsthatthismethodhashighaccuracy,anditcaneffectivelyimprovetheefficiencyofcustomerservicemanagementandreducecosts.
Keywords:Filtermodel,randomforest,telecommunicationscustomercomplaints,classification.
Introduction:
Withthedevelopmentoftelecommunicationstechnology,thetelecommunicationsindustryhasbecomeanimportantindustryforeconomicandsocialdevelopment.Telecommunicationsserviceshavegraduallybecomeanindispensablepartofpeople'slives,andcustomersatisfactionhasbecomeanimportantfactorinthedevelopmentoftelecommunicationscompanies.However,withtheincreaseinthenumberoftelecommunicationsusers,thenumberofcustomercomplaintsisalsoincreasingyearbyyear,whichputsagreatpressureoncustomerservicemanagement.Howtoclassifyandprocesscustomercomplaintsinatimelyandeffectivemannerhasbecomeanimportantissueincustomerservicemanagement.
Atpresent,thetraditionalcustomercomplainthandlingmethodismainlymanualprocessing,whichisnotonlytime-consumingandlabor-intensivebutalsopronetomistakes.Theapplicationofdataminingandmachinelearningtechnologycanhelptelecommunicationscompaniestoanalyzeandprocesslargeamountsofdataquickly,accurately,andeffectively.Inthispaper,weproposeaclassificationmethodfortelecommunicationscustomercomplaintsbasedontheFiltermodelandrandomforestalgorithm.Wepre-processandreducethedimensionalityofthecomplaintdatathroughtheFiltermodel,andthenusetherandomforestalgor