快速挖掘最大频繁项集算法在图书馆管理中的应用  

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

作　　者：于海洋 YU Hai-yang(Institute of Physical and Chemical Engineering of Nuclear Industry, Tianjin 300180, China)

机构地区：[1]核工业理化工程研究院,天津300180

出　　处：《计算机与现代化》2020年第6期68-72,共5页Computer and Modernization

基　　金：国家自然科学基金资助项目(21573072)。

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。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.

关 键 词：DS-Eclat算法 关联规则 最大频繁项集 个性化服务 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]