大数据时代高校图书馆读者服务工作策略研究

Research on reader service strategy of university library in big data era

指出大数据时代高校图书馆面临的困境,如云计算存在安全隐患,数据分析法能力有限,垃圾信息较多。给出了大数据时代高校图书馆读者服务路径,即运用数据分析挖掘技术进行文献资源建设,对馆藏资源点击率进行分析,利用图书馆自动化系统对馆藏资源进行合理分类,建立馆藏资源大数据系统和观察资源体系,根据读者需求进行科学决策,分析读者的阅读偏好、借阅习惯、借阅记录、检索历史等不同类型的半结构化和非结构化数据,建立以数据信息为基础的资源管理模式,设置特定岗位,利用大数据技术开展收集、整理、分析、集成、共享等相关工作。这样,才能充分发挥大数据技术的优势,深度挖掘和整合数据,积极更新服务理念,全面提升高校图书馆的服务质量和效率。

This paper points out the dilemma faced by university libraries in the era of big data,such as cloud computing has security risks,data analysis method has limited capacity,and there is more garbage information. It expounds the path of reader service in university libraries in the era of big data: using data analysis and mining technology to construct literature resources,analyzing the click-through rate of library resources,using library automation system to classify library resources reasonably,establishing large data system of library resources and observation resource system,making scientific decisions according to readers’ needs,and analyzing readers’ reading preferences. Different types of semi-structured and unstructured data,such as borrowing habits,borrowing records and retrieving history,are used to establish resource management model based on data information,set up specific posts,and use big data technology to collect,collate,analyze,integrate and share related work. Only in this way can we give full play to the advantages of big data technology,dig and integrate data in depth,actively update the service concept,and comprehensively improve the service quality and efficiency of university libraries.