2022年第46卷第10期132器件与应用artsandApplicationsP文献引用格式:贺晓琳.以用户兴趣为指导的个性化广播电视智能推荐系统[J].电声技术,2022,46(10):132-134,138.HEXL.Personalizedradioandtelevisionintelligentrecommendationsystemguidedbyuserinterests[J].AudioEngineering,2022,46(10):132-134,138.中图分类号:TN948.1文献标识码:ADOI:10.16311/j.audioe.2022.10.037以用户兴趣为指导的个性化广播电视智能推荐系统贺晓琳(河南工业和信息化职业学院,河南焦作454000)摘要:广播电视正朝着多样化和个性化的方向发展,使得用户很难在大量的广播电视节目中快速找到自己感兴趣的节目。因此,构建以用户兴趣为指导的个性化广播电视智能推荐系统成为必然。然而,用户的兴趣会随时间出现一定程度的变化,这就导致系统最终推荐的效果不尽如人意。因此,将兴趣随时间变化的趋势作为重要权重引入到协同过滤算法用户相似计算中,构建新型的广播电视推荐系统,最终通过实验验证,所提出的个性化广播电视智能推荐系统能够有效提升推荐结果的准确性。关键词:个性化;协同过滤;电视广播;智能推荐PersonalizedRadioandTelevisionIntelligentRecommendationSystemGuidedbyUserInterestsHEXiaolin(HenanCollegeofIndustry&InformationTechnology,Jiaozuo454000,China)Abstract:Radioandtelevisionaredevelopinginthedirectionofdiversificationandpersonalization,whichmakesitdifficultforuserstoquicklyfindtheprogramstheyareinterestedinamongalargenumberofradioandtelevisionprograms,soitisinevitabletobuildapersonalizedradioandtelevisionintelligentrecommendationsystemguidedbyusers'interests.However,users'interestswillchangetoacertainextentovertime,whichleadstounsatisfactoryresultsofthefinalrecommendationsystem.Therefore,thispaperintroducesthetrendofinterestchangeovertimeasanimportantweightintothecollaborativefilteringalgorithmusersimilaritycalculationtobuildanewtypeofbroadcastTVrecommendationsystem,andfinallyverifiesthroughexperimentsthatthepersonalizedbroadcastTVintelligentrecommendationsystemproposedinthispapercaneffectivelyimprovetheaccuracyofrecommendationresults.Keywords:personalization;collaborativefiltering;televisionbroadcast;smartrecommendations0引言随...