| 2009-2018年高校图书馆读者借阅规律演化探究——以北京大学图书馆为例 |
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| 引用本文： | 吴亚平,周春霞,张海舰.2009-2018年高校图书馆读者借阅规律演化探究——以北京大学图书馆为例[J].大学图书馆学报,2020(2):69-75. |
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| 作者姓名： | 吴亚平 周春霞 张海舰 |
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| 作者单位： | 北京大学图书馆 |
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| 摘 要： | 借书数据是图书馆特有的、规范性强、延续性强的读者数据之一,探究其中蕴含的图书馆资源利用规律的变迁和读者借阅倾向的演化,是了解读者、亲近读者从而优化图书馆服务的基础。聚焦北京大学图书馆2009—2018年的借书数据,通过聚类分析、时间演化分析等方法,挖掘读者借书时间、借书主题、热门作者的演化规律。结果显示,近十年来,图书馆的借书服务努力克服时空限制,推动常态化服务的效果显著;不同类别图书间的阅读差异有所缩小,跨学科阅读现象更为普遍;上升类热门作者的出现通常与社会事件、阅读推广活动有一定关联。基于此结论为图书馆的资源建设和服务优化提出有益参考,丰富了图书馆读者数据的价值挖掘研究。
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| 关 键 词： | 高校图书馆 借书数据 聚类分析 借阅规律 |
Research on the Evolution of Book Circulation Pattern in University Library from 2009to 2018——A Case Study of Peking University Library |
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| Wu Yaping,Zhou Chunxia,Zhang Haijian.Research on the Evolution of Book Circulation Pattern in University Library from 2009to 2018——A Case Study of Peking University Library[J].Journal of Academic Libraries,2020(2):69-75. |
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| Authors: | Wu Yaping Zhou Chunxia Zhang Haijian |
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| Abstract: | The circulation data is a kind of unique,normative and continuous user data of the library.It shows the change of library resource utilization and the evolution of users’borrowing behavior,which is the basis for optimizing library services.Based on the circulation data of Peking University Library from 2009 to 2018,this paper explores the characteristics of users’borrowing behaviors such as time,theme,and popular authors through cluster analysis and time evolution analysis.The results show that in the past ten years,the library’s circulation service has overcome the limitations of time and space to a certain extent,and the effect of promoting normalized services has been remarkable.The differences in reading among different types of books have been reduced,and the interdisciplinary reading has been continuously strengthened.The rising of popular authors is usually related to social events and reading promotion activities.It provides a useful reference for library resource construction and service optimization,and also enriches the value of library reader data mining and research. |
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| Keywords: | University Library Circulation Data Cluster Analysis Circulation Rules |
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