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1、RecomRecommenderPaulResnickandHalR.Varian,GuestEditorsSystemsTISOFTENNECESSARYTOMAKECHOICESWITHOUTSUFFICIENTIpersonalexperienceofthealternatives.Ineverydaylife,werelyonrecommendationsfromotherpeopleeitherbywordofmouth,rec-ommendationletters,movieandbookreviewsprintedinnewspapers,orSy
2、stgeneralsurveyssuchasZagat’srestaurantguides.RecommendersystemsassistandaugmentthisURLs;andSiteseerminespersonalbookmarklists.naturalsocialprocess.Inatypicalrecommendersys-Third,recommendationsmaybeanonymous,taggedtempeopleproviderecommendationsasinputs,withthesource’sidentity,ortag
3、gedwithapseudo-whichthesystemthenaggregatesanddirectstonym.Thefourthdimension,andoneoftherichestappropriaterecipients.Insomecasestheprimaryareasforexploration,ishowtoaggregateevaluations.transformationisintheaggregation;inotherstheGroupLens,PHOAKS,andSiteseeremployvariantssystem’sval
4、ueliesinitsabilitytomakegoodmatchesonweightedvoting.Fabtakesthatonestepfurthertobetweentherecommendersandthoseseekingrecom-combineevaluationswithcontentanalysis.Referral-mendations.WebcombinessuggestedlinksbetweenpeopletoformThedevelopersofthefirstrecommendersystem,longerreferralchai
5、ns.Finally,the(perhapsaggregated)Tapestry[1],coinedthephrase“collaborativefiltering”evaluationsmaybeusedinseveralways:negativerec-andseveralothershaveadoptedit.Wepreferthemoreommendationsmaybefilteredout,theitemsmaybegeneralterm“recommendersystem”fortworea-sortedaccordingtonumericeva
6、luations,orsons.First,recommendersmaynotexplictlyevaluationsmayaccompanyitemsinadis-collaboratewithrecipients,whomaybeplay.unknowntoeachother.Second,recom-Figures2and3identifydimensionsmendationsmaysuggestparticularlyofthedomainspace:Thekindsofinterestingitems,inadditiontoindicat-ite
7、msbeingrecommendedandtheingthosethatshouldbefilteredout.peopleamongwhomevaluationsareThisspecialsectionincludesdescrip-shared.Consider,first,thedomainoftionsoffiverecommendersystems.Asixthitems.Thesheervolumeisanimportantarticleanalyzesincentivesforprovisionofrec-variable:Detailedtex
8、tualreviewso
