摘要
运用K-means算法,对福建工程学院图书馆管理系统中学生借阅信息进行数据挖掘。通过分析不活跃学生、一般学生和活跃学生3类读者的借阅规律,对馆藏结构进行优化,以期提升图书馆的资源利用率和管理工作效率,更好地为读者提供个性化服务。
The paper mines student＇s borrowing data in the library management systems of Fujian University of Technology using the K-means algorithm. Through analysis of borrowing rules of inactive students, general students and active students, it puts forward an optimized scheme for the structure of library collection, to enhance efficiency of resource utilization and management of library, and serve the reader better with personalized services.
出处
《情报探索》
2013年第1期97-99,共3页
Information Research
关键词
K-MEANS
聚类算法
读者聚类挖掘
图书聚类挖掘
个性化服务
K-means
clustering algorithm
clustering mining of reader
clustering mining of books
personalized service
