北京邮电大学学报(社科版) ›› 2016, Vol. 18 ›› Issue (1): 14-19.

• 网络文化 • 上一篇    下一篇

图书馆借阅数据分类信息的关联性研究

  

  1. 1北京邮电大学 经济管理学院,北京100876;2国家图书馆 信息技术部, 北京100081
  • 收稿日期:2015-11-08 出版日期:2016-02-28
  • 基金资助:

    文化部科技创新项目(2013kjcxxm09)

Associations Between Different Classifications of Library Circulation Data

  1. 1 School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing
    100876, China;2 Information and Technology Department, National Library of China, Beijing 100081, China
  • Received:2015-11-08 Online:2016-02-28

摘要:

图书馆如何分类排架,方便读者寻找感兴趣的图书,对构建以读者为中心的图书馆,具有重要的实践意义。在分析了关联规则数据挖掘技术的基础上,结合国家图书馆RFID技术应用实践,探讨了利用Apriori关联规则数据挖掘技术对读者借阅的图书分类信息进行关联挖掘的方法。从国家图书馆业务自动化集成系统中随机抽取读者借阅历史数据,编写了java程序,对样本数据进行了挖掘,并对挖掘结果进行了分析。研究表明,国家图书馆读者借阅文学、历史和技术类图书文献较多,关联度高,适当调整这几类书籍排架位置将会方便读者借阅。

关键词: 借阅数据, 数据挖掘, 图书分类, 关联规则, Apriori算法

Abstract:

How the library classifies and arranges books to facilitate readers’ search is of great significance to constructing a readeroriented library On the basis of analyzing data mining techniques based on association rules, combined with RFID application in the National Library of China(NLC), a method of applying Apriori association rules to classify and analyze library circulation data is discussed In order to remedy the defections of Apriori association method, two solutions are applied for optimizing purpose and the optimized algorithm is presented and explained in detail By using the historical circulation records gathered from the Library Integration System of NLC, empirical study of the algorithm is made with java program languages and finally the result analysis is given Study shows that the readers of NLC more like to borrow literature, history and technology books, and the appropriate adjustment of the position of these books will bring greater convenience to readers

Key words: circulation data, data mining, association rules, Apriori algorithm

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