现代电子技术2018，Vol.41Issue(6)：34-36,3.DOI:10.16652/j.issn.1004-373x.2018.06.008
基于读者个性化特征数据挖掘的图书馆书目推荐
Library catalogue recommendation based on readers′ personalized feature data mining
摘要
Abstract
The traditional library service lacks personalized setting,and cannot make full use of resources to conduct cata-logue recommendation accurately. To resolve this problem,library catalogue recommendation based on readers′ personalized fea-ture data mining is proposed. According to reader clustering characteristics and data association rules,a personalized program recommendation system is designed,and the mined association rules are applied to recommendation service. A large amount of data can be obtained according to the mining process,with redundant data cleaned and incomplete data supplemented,so as to calculate the support degree and confidence coefficient. Readers′ personalized feature data is used to mine and recommend li-brary catalogue,so as to complete library catalogue recommendation. The experimental analysis shows that this recommendation method can make full use of library resources and complete catalogue recommendation quickly and accurately.关键词
图书馆服务/个性化特征/数据关联规则/数据挖掘/图书馆书目/书目推荐Key words
library service/personalized feature/data association rule/data mining/library catalogue/catalogue recommen-dation分类
信息技术与安全科学引用本文复制引用
谢康..基于读者个性化特征数据挖掘的图书馆书目推荐[J].现代电子技术,2018,41(6):34-36,3.
