摘要
以南开大学图书馆Unicorn系统为基础,介绍基于最大频繁模式挖掘算法的书目推荐系统的设计与实现,详细描述利用Unicorn系统中积累的借阅数据分析读者的行为模式,提供个性化书目推荐的方法。该系统利用图书馆现有资源拓展读者服务,可以提高现行自动化借阅系统的使用效率。
On the foundation of the Unicorn system in Nankai University Library, this paper introduces the design and implementation of bibliographic recommendation system based on maximal frequent patterns mining algorithm. It describes the process of analyzing the readers＇ behavior patterns by fully utilizing the accumulation data collected in the Unicorn system in details, so as to offer personalized bibliographic recommendation service. By using this system, the academic library can effectively expand different service patterns to readers on available sources, and improve the efficiency of the existing automated circulation system.
出处
《现代图书情报技术》
CSSCI
北大核心
2010年第5期23-28,共6页
New Technology of Library and Information Service
关键词
个性化书目推荐
数据挖掘
频繁模式树
最大频繁模式
频繁模式增长
Personalized bibliographic recommendation Data mining Frequent pattern tree （FP -Tree） Maximal frequent patterns FP - Growth
