计算机与现代化 ›› 2020, Vol. 0 ›› Issue (06): 68-.

• 数据挖掘 • 上一篇    下一篇

快速挖掘最大频繁项集算法在图书馆管理中的应用

    

  1. (核工业理化工程研究院,天津300180)
  • 收稿日期:2019-10-16 出版日期:2020-06-24 发布日期:2020-06-28
  • 作者简介:于海洋(1979-),男,天津人,高级图书馆员,本科,研究方向:图书管理,E-mail: dyrqpg324387@126.com。
  • 基金资助:
    国家自然科学基金资助项目(21573072)

Application of Algorithm of Fast Mining Maximal Frequent Itemsets in Library Management

  1. (Institute of Physical and Chemical Engineering of Nuclear Industry, Tianjin 300180, China)
  • Received:2019-10-16 Online:2020-06-24 Published:2020-06-28

摘要: 针对图书馆服务方式的滞后,图书馆与用户供需矛盾的现状,运用数据挖掘技术,调取借阅记录,采用DS-Eclat算法,挖掘其最大频繁项集,通过找出用户搜索信息中的内在关联规则,以此促进图书馆服务方式的转变。对比传统Eclat算法与本文DS-Eclat算法,结果表明DS-Eclat算法能很快地发现最大频繁项集,此最大频繁项集能促进图书馆个性化服务的发展。

关键词: DS-Eclat算法, 关联规则, 最大频繁项集, 个性化服务

Abstract: Aiming at the lag of librarys service mode and the contradiction between librarys supply and users demand, this paper uses data mining technology and DS-Eclat algorithm to mine its maximum frequent item set by borrowing records, and to promote the transformation of librarys service mode by finding out the internal association rules in users searching information.By comparing the traditional Eclat algorithm with the DS-Eclat algorithm in this paper, it is shown that the DS-Eclat algorithm can quickly discover the maximum frequent item set, and the maximum frequent item set can promote the development of library personalized service.

Key words: DS-Eclat algorithm, association rule, maximum frequent itemsets, individualization service

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