I摘要网络信息技术的高速发展，使得高校图书馆的服务空间日益扩大，依据个人特点的针对性服务逐渐成为新服务模式的主导趋势。对于大多数用户而言，很难在大量的学术图书馆中快速找到他们想要的材料。另外，随着时代的不断发展，越来越多的新兴学科，学科的融合更是普遍。各种专业知识的爆炸性增长使大学图书馆必须扩大书籍的储存量，这是为建立和实施图书馆定制推荐系统提供了基本条件。个性化图书推荐服务改变传统图书馆被动服务方式，能根据用户的兴趣偏好主动地向用户推荐图书。本文的重点是依据用户的多样需求追踪图书的最近资源，且及时告知用户，实现个性化的服务，且提高资源的使用效果，改变图书馆的服务模式。从被动到主动。协同过滤推荐算法的实现，可以让大学的师生们更方便快捷，且准确的得到自己需要的书目。从而避免了搜索时间造成的浪费。本文所做的工作主要包括以下几点：（1）本文提出了对冷启动问题的优化、对数据稀疏性问题的完善、对缺失数据的处理操作。（2）本文既说明了涉及的相关技术，同时进行了可行性和准确性评估，并讨论了个人定制书籍推荐中使用的推荐算法和混合算法。（3）本文结合推荐系统的实际需求程度，基于SpringBoot的图书推荐系统的研究与实现。关键词：SpringBoot、推荐算法、LFMIIAbstractWiththerapiddevelopmentofnetworkinformationtechnology,theservicespaceofuniversitylibraryisexpandingdaybyday,andpersonalizedservicehasgraduallybecomethemainstreamofnewservicemode.Formostusers,itisdifficulttofindtheinformationtheyneedinthelargecollectionofuniversitylibrary.Inaddition,withthecontinuousdevelopmentofthetimes,therearemoreandmorenewmajors,andtheprofessionalintegrationisbecomingstrongerandstronger.Theexpansionofallkindsofprofessionalknowledgemakesuniversitylibrarieshavetoexpandtheirownknowledgestorage,whichalsoprovidesthebasicconditionsfortheconstructionandimplementationoflibrarypersonalizedrecommendationsystem.Personalizedbookrecommendationservicehaschangedthepassiveservicemodeoftraditionallibrary,whichcanactivelyrecommendbookstousersaccordingtotheirinterests.Theproblemtobesolvedinthispaperistotrackthelatestlibraryresourcesaccordingtothedifferentneedsofusers,informusersatthefirsttime,realizetheoptimizationofpersonalizedserviceandresourceutilization,andchangethelibraryservicemodefrompassivetoactive.Collaborativefilteringrecommendationalgorithmenablescollegeteachersandstudentstofindtheknowledgebookstheyneedmoreaccuratelyandfaster,reducesthesearchpressureofthelibraryandsavesalotoftime.Theworkofthispapermainlyincludesthefollowingpoints.(1)Inthispaper,theoptimizationofcoldstart,theimprovementofdatasparsityandtheprocessingofmissingdataareproposed.(2)Thispaperdiscussesthetechnologyinvolved,analyzesitsfeasibilityandaccuracy,anddiscussesthepersonalizedbookrecommendationalgorithmandhybridalgorithm.(3)Combinedwiththeactualdemandlevelofbookrecommendationsystem,thispaperstudiesandimplementsaBookRecommendationSystemBasedonspringboot.Keywords:SpringBoot，recommendationalgorithm,LFMIII目录摘要....................................................................................................................................IAbstract.....................................................................................................................................II目录..................................................................................................................................III图目录.....................................................................................................................................VI表目录......
