快速挖掘最大频繁项集算法在图书馆管理中的应用

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。

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

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.