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ID:33677670
大小:6.75 MB
页数:68页
时间:2019-02-28
《基于组合推荐技术的音乐推荐引擎-研究与实现》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、万方数据广东工业大学硕士学位论文协同过滤算法。3.后台离线整合两种算法的推荐结果,在线推荐模块实时优化用户的推荐列表,从而实现个性化音乐推荐引擎系统。为了增强了用户的体验,』HjMongoDB加速数据的存取,用Spring搭建高效的后台系统,用Bootstrap和HTML5增强前台页面的视听效果,使我们的系统能应用在实际需求中。关键词:协同过滤;组合推荐;SimhashHadoop:MahoutⅡ万方数据Absn'actAbstractWhilepeoplegetmusicbyavarietyofways,mostofthemli
2、stenformtheInteract.Thebusymodemlifeandthevastnetworkresourcesmakealotofpeopletoobusytosearchtheirfavoritemusiccarefully,andalotofuserfavoritemusichasnochancetobeenjoyed.Howtodiscoveryuserfavorquicklyandhelpuserstofmdtheirfavoritemusic,whichisthejobofmusicrecommendati
3、onengine.RecommendationalgorithmistheCOreoftheengine,themeritsofthealgorithmdeterminesthequalityoftherecommendationresult.Theresearchofcontent-basedrecommendationalgorithmhasstartedinanearlytime.Thispaperuselabelstodescribemusicdata,makingitcanbeusedincontent—basedrec
4、ommendationalgorithmwhichismainlyclusteringalgorithm.thetraditionalTF·IDFalgorithmgeneratemusicdocumentvectorforclustering,notonlyhasalowefficiency,butabadrecommendationeffect.Therefore,thispaperputsforwardanewalgorithmforgeneratingvectors,whichuseSimhashalgorithmtocr
5、eatethefingerprintcharacteristicvaluefortheitemstOcluster.Thismethodgetsahighefficiencyandabetterclusteringeffectbytheexperiments.Inaddition,inthefieldofrecommendation,collaborativefilteringalgorithmisthemorewidelyappliedatpresent.Accordingtothecharacteristicsofthecol
6、laborativefilteringrecommendationalgorithmhaslargecalculationamount,thispapermainlytalksaboutimplementinguser—baseddistributedcollaborativefilteringalgorithmontheHadoopplatform,optimizingusermatrix,removinghotorcolditemsandsimplifyingthewholeprocess.Intheexperiments,c
7、omparedwithitem-baseddistributedcollaborativefilteringalgorithm,inthepremiseofsamedatasize,collaborativefilteringalgorithmhadafasterspeed.What’Smore,it’Squalitydidnotbecomeworse.Finally,thispaperbuiltamusicalrecommendationengineprototypesystemwithB/Sstructure,integrat
8、edtheresultofoffiinerecommendationalgorithmandaddedonlinerecommendationfunction,whichmeetsthereal.timeneedoftheusersandhelps
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