摘要
[目的/意义]从用户兴趣建模、推荐机制、信息资源管理3方面阐述国内基于大数据的信息推荐核心内容研究进展。[方法/过程]文章用内容分析法归纳了263篇文献内容,从用户兴趣建模、推荐机制、信息资源管理3方面阐述了国内基于大数据的信息推荐核心内容研究进展。[结果/结论]基于大数据的用户兴趣建模主要结合大数据技术改进传统用户兴趣建模,包括模型表示、模型初始化和模型进化;基于大数据的推荐机制主要改进、混合传统推荐机制并优化推荐结果;基于大数据的信息资源管理包括数据采集、数据挖掘、数据表示、数据存储和数据更新。
[Purpose/Significance]In order to reveal research development on core content of information recommendation based on big data in China from three aspects of user interest modeling,recommendation mechanism and information resource management.[Method/Process]Using the content analysis method,the authors summarized the content of the 263 articles,and expounded the core content research development of information recommendation based on big data in China from three aspects of user interest modeling,recommendation mechanism and information resource management.[Result/Conclusion]User interest modeling based on big data mainly improved traditional user interest modeling with big data technology.It included model representation,model initialization and model evolution.The recommendation mechanism based on big data mainly reforms,combined the traditional recommendation mechanism and optimized recommendation outcome.The information resources management based on big data included data collection,data mining,data representation,data storage and data update.
作者
孙雨生
朱金宏
李亚奇
Sun Yusheng;Zhu Jinhong;Li Yaqi(School of Economics and Management,Hubei University of Technology,Wuhan 430068,China;School of Vocational and Technical Teachers,Hubei University of Technology,Wuhan 430068,China)
出处
《现代情报》
CSSCI
2020年第8期156-165,共10页
Journal of Modern Information
基金
教育部人文社会科学研究规划基金项目“基于本体的数字图书馆语义用户兴趣模型构建机理及应用模式研究”(项目编号:17YJA870016)
中国博士后科学基金项目“基于领域本体的数字图书馆用户兴趣建模研究”(项目编号:2014M560107)
湖北省社会科学基金项目“语义网格环境下数字图书馆个性化推荐机制及其应用研究”(项目编号:2015108)。
关键词
大数据
信息推荐
用户兴趣建模
信息资源管理
个性化
big data
information recommendation
user interest modeling
information resource management
personalization
