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1、WithaLittleHelpFromMyFriends:GeneratingPersonalizedBookRecommendationsUsingDataExtractedfromaSocialWebsiteMariaSoledadPeraYiu-KaiNgComputerScienceDepartmentBrighamYoungUniversityProvo,Utah,U.S.A.Abstractmationtoinferusers'interestsandpreferences.Thesekindsofinformationareuniqueandvaluableformaking
2、recom-Withthelargeamountofbooksavailablenowadays,mendationsonbooks,movies,newsarticles,etc.,whichusersareoverwhelmedwithchoiceswhentheyattempttohavebeenexaminedin[2,3,9].Newly-developedrec-findbooksofinterest.Whileexistingbookrecommendationommenders,suchas[9,16,22],incorporatedataextractedsystems,w
3、hicharebasedoneithercollaborativefiltering,fromsocialwebsitestoincreasethequalityoftag,newscontent-based,orhybridmethods,suggestbooks(amongarticles,andbookrecommendations.Bookrecommendersthemillionsavailable)thatmightbeappealingtotheusers,havebeenadoptedbyonlineshoppingcompanies,socialtheirrecommen
4、dationsarenotpersonalizedenoughtomeetwebsites,anddigitallibraries,tonameafew,tofurtherusers'expectationsduetotheircollectiveassumptiononfacilitatetheirusers'knowledgeacquisitionprocessbyof-grouppreferenceand/orexactcontentmatching,whichisferingalternativechoices(amongthemillionsavailable)ofafailur
5、e.Toaddressthisproblem,wehavedevelopedbookstheyarelikelyinterestedin.Whilesuggestionspro-PReF,aPersonalizedRecommenderthatreliesonFriend-videdbyexistingbookrecommenderscanintroduceusersshipsestablishedbyusersonasocialwebsite,suchasLi-tobooksthattheyarenotawareof,theserecommendersarebraryThing,toma
6、kebookrecommendationstailoredtoin-notpersonalizedenoughtoachievetheirdesigngoals[10].dividualusers.InselectingbookstoberecommendedtoaItisimperativetodeveloppersonalizedrecommendersthatuserU,whoisinterestedinabookB,PReF(i)considersprovidefinersuggestionspertinenttoindividualusers'in-booksbelongedtoU
7、'sfriends,(ii)appliesword-correlationterestsorpreferences.Tothebestofourknowledge,therefactorstodisclosebookssimilarincontentstoB,(iii)de-arenorecommendationsystemsthatsimultaneouslycon-pendsontheratingsgiventobo
