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1、WWW2008/PosterPaperApril21-25,2008·Beijing,ChinaImprovingPersonalizedServicesinMobileCommercebyaNovelMulticriteriaRatingApproachQiudanLi,ChunhengWang,GuanggangGengKeyLaboratoryofComplexSystemsandIntelligenceScience,InstituteofAutomation,ChineseAcademyofSciences,Beijing{q
2、iudan.li,chunheng.wang,guanggang.geng}@ia.ac.cnABSTRACTInspiredbythetechniqueofmulti-dimensionalcollaborativefilteringine-commerce[4],weproposeanovelMSVD-basedCFWiththerapidgrowthofwirelesstechnologiesandmobileapproachtopersonalizedservicesinm-commerce,whichdevices,there
3、isagreatdemandforpersonalizedservicesinm-incorporatescontextualinformationandmulticriteriaratingsintocommerce.Collaborativefiltering(CF)isoneofsuccessfultherecommendationprocessandenrichesourpreviouswork[1].techniquestoproducepersonalizedrecommendationsforThebasicideaoft
4、hispaperistofirstidentifysimilarcontextualusers.ThispaperproposesanovelapproachtoimproveCFinformationtothatoftheactivemobileuser,andthenrecognizealgorithms,wherethecontextualinformationofauserandthethenearestneighborsoftheuserbasedontheMSVDtechniquemulticriteriaratingsof
5、anitemareconsideredbesidesthetypicalundersomerelevantcontextinformation,andatlastperforminformationonusersanditems.Themultilinearsingularvaluepersonalizedservicesbasedonthosefoundsimilarneighbors.decomposition(MSVD)techniqueisutilizedtoexplorebothWithinthisframework,a3-o
6、rdertensorisusedtorepresenttheexplicitrelationsandimplicitrelationsamonguser,itemandcriterion.Weimplementtheapproachinanexistingm-commerce3DUser×Item×Criteriondata,andthetruncatedMSVDplatform,andencouragingexperimentalresultsdemonstrateitstechniqueisutilizedtoexploretheu
7、nderlyingrelationsamongeffectiveness.user,itemandcriterion.Theframeworkcantakefulladvantagesofthemulti-dimensionalrepresentationcapabilityofahigher-ordertensor,theapproximationcapabilityoftheMSVD,andtheCategoriesandSubjectDescriptorsfunctionofcollaborativefiltering.H.2.8
8、[DatabaseApplications]:Datamining;H.3.5[OnlineInformationServices]:Web-basedservices.2.ANOVELCOLLABORAT
