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1、CoupledGroupLassoforWeb-ScaleCTRPredictioninDisplayAdvertisingLingYanYLING0718@SJTU.EDU.CNShanghaiKeyLaboratoryofScalableComputingandSystems,DepartmentofComputerScienceandEngineering,Shang-haiJiaoTongUniversity,ChinaWu-JunLiLIWUJUN@NJU.EDU.CNNationalKeyLaborat
2、oryforNovelSoftwareTechnology,DepartmentofComputerScienceandTechnology,NanjingUniversity,ChinaGui-RongXueGRXUE@ALIBABA-INC.COMAlibabaGroup,ChinaDingyiHanDINGYI.HAN@ALIBABA-INC.COMAlibabaGroup,ChinaAbstract1.IntroductionRecently,onlineadvertisinghasbecomethemos
3、tpopularIndisplayadvertising,clickthroughrate(CTR)andeffectiveapproachtodobrandpromotionandproduc-predictionistheproblemofestimatingtheprob-tmarketing.Itisamulti-billionbusinessonthewebandabilitythatanadvertisement(ad)isclickedwhenaccountsforthemajorityofthein
4、comeforthemajorinter-displayedtoauserinaspecificcontext.Duenetcompanies,suchasGoogle,YahooandAlibaba.Dis-toitseasyimplementationandpromisingperfor-playadvertisingisabigpartofonlineadvertisingwheremance,logisticregression(LR)modelhasbeenadvertiserspaypublishersf
5、orplacinggraphicaladvertise-widelyusedforCTRprediction,especiallyinin-ments(ads)onpublishers’webpages(Chapelleetal.,dustrialsystems.However,itisnoteasyforLR2013).Thepublishersallocatesomepositionsontheirwebtocapturethenonlinearinformation,suchasthepagesandsell
6、themtodifferentadvertisers.Usersvisittheconjunctioninformation,fromuserfeaturesandwebpagesandcanviewthepublishedads.Therearesomeadfeatures.Inthispaper,weproposeanov-otherroles,suchasadagenciesandpublishernetworks,toelmodel,calledcoupledgrouplasso(CGL),forcompo
7、sethecomplexadvertisingsystem(Muthukrishnan,CTRpredictionindisplayadvertising.CGLcan2009).Butthatisnotthefocusofthispaper.Sowewilljustseamlesslyintegratetheconjunctioninformationfocusonthescenarioswithauser-advertiser-publishertri-fromuserfeaturesandadfeatures
8、formodeling.partitebusiness,inwhichthreepartieshaveseparategoalsFurthermore,CGLcanautomaticallyeliminatethatcanbereducedtoaunifiedtaskintheend.Thead-uselessfeaturesforbothusersandad