Article(id=1242135560869978638, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242135527122608532, articleNumber=null, orderNo=22, doi=10.3981/j.issn.1000-7857.2016.23.014, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1474214400000, receivedDateStr=2016-09-19, revisedDate=1476288000000, revisedDateStr=2016-10-13, acceptedDate=null, acceptedDateStr=null, onlineDate=1482909876437, onlineDateStr=2016-12-28, pubDate=1481558400000, pubDateStr=2016-12-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1482909876437, onlineIssueDateStr=2016-12-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774077795470, creator=sys-migrate, updateTime=1774077795470, updator=sys-migrate, issue=Issue{id=1242135527122608532, tenantId=1146029695717560320, journalId=1146031591421210625, year='2016', volume='34', issue='23', pageStart='1', pageEnd='148', issueExtLink='null', onlineDate='null', pubDate='1481558400000', pubDateStr='2016-12-13', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774077787424, creator='sys-migrate', updateTime=1774077787424, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=127, endPage=136, ext={EN=ArticleExt(id=1242135566595207799, articleId=1242135560869978638, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=A mobile library recommendation system based on Internet of Things and indoor location, columnId=1242116080374710456, journalTitle=Science & Technology Review, columnName=Articles, runingTitle=null, highlight=null, articleAbstract=In order to take the advantages of new technology such as the Internet of Things and the indoor location, and make full use of the characteristics of library, a mobile library recommendation system is designed and developed. System data is collected by using the NFC in the Internet of Things. Then, the item-based collaborative filtering recommendation and the hot recommendation, which respectively use Mahout and Redis, are mixed and weighted to get a list of recommended books. The position of the reader is obtained by the position fingerprint location method. Accordingly, a mixed recommendation result is presented to the reader. At the same time reader's feedback is designed to optimize the recommendation, therefore, the recommendation system can better serve the reader., authors=YE Xiaorong¹, SHAO Qing², authorsList=YE Xiaorong, SHAO Qing, authorCompany=1. Institute of Scientific and Technical Information of China, Beijing 100038, China;
2. KNET Co., Ltd., Beijing 100190, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=wZfKSNOogRekvjT8slm0Uw==, pdfFileSize=5084513, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242135565362082412, articleId=1242135560869978638, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=结合物联网和室内定位的手机图书馆推荐系统, columnId=1146540929516700224, journalTitle=科技导报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=为利用物联网和室内定位等新技术的优势，并充分利用图书馆的特点，设计开发了结合物联网和室内定位的手机图书馆推荐系统。借助物联网中的近场通信（NFC）搜集了系统数据；利用Mahout和Redis实现了基于物品的协同过滤推荐和基于热点的推荐，并将2种推荐的结果混合推荐计算得到推荐图书列表；利用位置指纹定位法得到读者的实时位置，以此向读者推送推荐结果，同时根据用户的反馈优化推荐结果。通过这些优化和改进，可使图书馆更好地为读者服务。, authors=叶小榕¹, 邵晴², authorsList=叶小榕, 邵晴, authorCompany=1. 中国科学技术信息研究所, 北京 100038;
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