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基于改进用户兴趣模型的个性化图书推荐算法（英文）.docx

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基于改进用户兴趣模型的个性化图书推荐算法（英文） Title:PersonalizedBookRecommendationAlgorithmbasedonanEnhancedUserInterestModel Abstract: Therapidgrowthofonlinebookstoresanddigitallibrarieshasmadeitincreasinglychallengingforuserstodiscoverrelevantbooksthatmatchtheiruniqueinterests.Accordingly,personalizedbookrecommendationalgorithmshavebecomecrucialforenhancingtheuserexperienceandincreasingbooksales.Thispaperproposesapersonalizedbookrecommendationalgorithmthatbuildsuponanimproveduserinterestmodel.Thealgorithmenhancestheaccuracyandprecisionofbookrecommendationsbyincorporatinguserdemographics,browsingandpurchasehistory,andcollaborativefilteringtechniques.Experimentalresultsdemonstratetheeffectivenessandefficiencyoftheproposedalgorithminprovidingpersonalizedbookrecommendations. 1.Introduction Withtheproliferationofonlinebookstoresandtheincreasingavailabilityofdigitallibraries,personalizedbookrecommendationalgorithmshaveemergedasindispensabletoolsforassistingusersindiscoveringrelevantbooks.Traditionalbookrecommendationalgorithmsoftenrelysolelyonthebookcontentorcollaborativefilteringtechniqueswithoutconsideringtheuser'sspecificinterestsorcharacteristics.Thispaperpresentsanovelapproachtoimproveuponthislimitationbyincorporatingarefineduserinterestmodel,whichcombinesuserdemographics,browsingandpurchasehistory,andcollaborativefilteringtechniques. 2.RelatedWork Thissectionreviewstheexistingliteratureonbookrecommendationalgorithms,focusingoncollaborativefiltering,content-basedfiltering,andhybridapproaches.Italsodiscussestheimportanceofincorporatinguserdemographicsandbrowsinghistoryinpersonalizedbookrecommendations. 3.EnhancedUserInterestModel Theproposedalgorithmstartsbyconstructinganenhanceduserinterestmodelthatencompassesmultipledimensionsofuserpreferences.Thismodelincorporatesuserdemographics,suchasage,gender,andlocation,whichhavebeenshowntosignificantlyimpactusers'bookpreferences.Additionally,thealgorithmconsiderstheuser'sbrowsingandpurchasehistorytocaptureimplicituserpreferences.Thesetwocompone