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ID:34084497
大小:2.59 MB
页数:38页
时间:2019-03-03
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1、RWTHAachenUniversityUniversityofBonnFraunhoferFITE-CommerceSeminarWT08/09RecommenderEnginesSeminarPaperThomasHess(289222)February1,2009AbstractRecommenderenginesareusedbymoreandmoree-commercebusinessestohelpcon-sumersfindingproductstheyareinterestedin.Thepaperdescrib
2、eswhatrecommenderenginesareandwhatroletheyplayine-commerce.Recommenderenginesusevarioustechniquesthatusedif-ferentknowledgesourcestomakerecommendations.Thepaperexplainsthesetechniquesandtheirstrengthsandweaknesses.Someofthecommonissuesthatrecommendersystemsfacearedi
3、scussedandpossiblesolutionspresented.Concludingexamplesofrecommenderenginesine-commercearedescribed.Itisshownwhattechniquestheyuseandhowthee-businessesutilizerecommendationsontheirwebsites.Contents1Introduction52RecommenderTechniques62.1Non-PersonalizedRecommendatio
4、n..........................62.2DemographicRecommendation............................72.3Content-BasedRecommendation............................82.4CollaborativeFiltering.................................92.4.1User-BasedApproach.............................102.4.2Item
5、-BasedApproach.............................102.4.3Model-BasedApproach............................122.5HybridApproaches...................................133IssuesAndSolutions143.1DataCollection.....................................143.2ColdStart......................
6、..................143.3Stabilityvs.Plasticity..................................153.4Sparsity.........................................153.5Performance&Scalability...............................163.6UserInputConsistency.................................173.7Privacy....
7、.....................................174RecommenderEngineExamples194.1ChoiceStream......................................204.2Amazon.com......................................224.3Digg...........................................295Conclusion363ListofFigures2.1Knowledge
8、SourcesofRecommenderEngines.....................62.2Non-PersonalizedRecommendation..........................72.3DemographicRecommendation.
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