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1、CollaborativeFilteringwithTemporalDynamicsYehudaKorenYahoo!Research,Haifa,Israelyehuda@yahoo-inc.comABSTRACTtemporaryeffectsthathaveverylowimpactonfuturebehavior,Customerpreferencesforproductsaredriftingovertime.Productwhilecapturinglonger-termtrendsthatreflecttheinhere
2、ntnatureperceptionandpopularityareconstantlychangingasnewselec-ofthedata.Thisledtomanyworksontheproblem,whichisalsotionemerges.Similarly,customerinclinationsareevolving,lead-widelyknownasconceptdrift;seee.g.[15,25].ingthemtoeverredefinetheirtaste.Thus,modelingtemporaldy
3、-Modelingtemporalchangesincustomerpreferencesbringsuniquenamicsshouldbeakeywhendesigningrecommendersystemsorchallenges.Onekindofconceptdriftinthissetupistheemergencegeneralcustomerpreferencemodels.However,thisraisesuniqueofnewproductsorservicesthatchangethefocusofcusto
4、mers.Re-challenges.Withintheeco-systemintersectingmultipleproductslatedtothisareseasonalchanges,orspecificholidays,whichleadandcustomers,manydifferentcharacteristicsareshiftingsimulta-tocharacteristicshoppingpatterns.Allthosechangesinfluencetheneously,whilemanyoftheminflu
5、enceeachotherandoftenthosewholepopulation,andarewithintherealmoftraditionalstudiesonshiftsaredelicateandassociatedwithafewdatainstances.Thisconceptdrift.However,manyofthechangesinuserbehavioraredistinguishestheproblemfromconceptdriftexplorations,wheredrivenbylocalizedf
6、actors.Forexample,achangeinthefamilymostlyasingleconceptistracked.Classicaltime-windoworinstance-structurecandrasticallychangeshoppingpatterns.Likewise,indi-decayapproachescannotwork,astheylosetoomuchsignalwhenvidualsgraduallychangetheirtasteinmoviesandmusic.Allthosedi
7、scardingdatainstances.Amoresensitiveapproachisrequired,changescannotbecapturedbymethodsthatseekaglobalconceptwhichcanmakebetterdistinctionsbetweentransienteffectsanddrift.Instead,foreachcustomerwearelookingatdifferenttypeslongtermpatterns.Theparadigmweofferiscreatingam
8、odelofconceptdrifts,eachoccursatadistincttimeframeandisdriventrackingthetimechangingbehaviorthroughoutthelifespanofth
