摘要
为应对高校图书馆用户普遍面临的"信息过载"和"信息迷航"问题,提高图书馆专题信息服务质量和优化资源的有效利用,文章采用数据挖掘和数据推荐技术,构建了一个高校图书馆个性化专题推送服务模型,并应用该模型对广西某高校图书馆MELINETS II系统中大量的查询借阅日志记录进行了挖掘和分析,以便为高校图书馆用户指引及时、准确、适宜的资源,并提供更具人性化和针对性的个性化信息服务。
In response to the common problems that university library users face such as information overloading and information-mazing, and to improve the thematic information service of university libraries and optimize the effective utilization of resources, this paper constructs a model of personalized topic recommendation service in university libraries by using data mining and data recommendation techniques. Finally, it applies the model mentioned above to the mining and analyzing of large numbers of query and circulation log records of MELINETS II system used in a university library of Guangxi province so as to guide a kind of timely, accurate, and suitable resources and provide more human and targeted personalized i nformat ion services for university library users.
出处
《图书馆学研究》
CSSCI
北大核心
2012年第13期53-58,24,共7页
Research on Library Science
基金
2010年度国家社会科学基金项目"高校图书馆个性化服务系统开发研究"(批准号:10BTQ008)的研究成果之一
关键词
个性化专题推荐
高校图书馆
数据挖掘
personalized topic recommendation university libraries data mining
