高校图书馆读者借阅行为实证研究——以西南财经大学天府学院图书馆为例

摘要

The paper bases on massive data on reader borrowing behavior in library information management system, uses associa-tion mining technology and Microsoft association algorithm to elaborate how to find hidden regular knowledge in reader behavior data, so as to provide the basis for library management. The paper proposes to optimize collection construction to guide the next purchase plan, guide library managers to screen types of document scientifically to recommend new and popular books, and place books with strong correlation centrally.%基于图书馆信息管理系统中积累的大量读者借阅行为数据,通过关联挖掘技术,使用Microsoft关联规则算法,结合实例,阐述如何发现读者行为数据中隐藏的规律性知识,为图书馆管理提供依据.提出应优化馆藏建设,指导下一步采购计划；指导图书馆管理人员对文献种类进行科学筛选,进行新书推荐和热门图书推荐；在对书籍进行排架时可以把关联性强的图书尽量集中放置等建议.