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Library personalized recommendation service method based on improved association rules

机译:基于改进关联规则的图书馆个性化推荐服务方法

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Purpose Nowadays, database management system has been applied in library management, and a great number of data about readers' visiting history to resources have been accumulated by libraries. A lot of important information is concealed behind such data. The purpose of this paper is to use a typical data mining (DM) technology named an association rule mining model to find out borrowing rules of readers according to their borrowing records, and to recommend other booklists for them in a personalized way, so as to increase utilization rate of data resources at library.
机译:目的现在,数据库管理系统已应用于库管理中,并且有大量关于读者访问资源的历史记录的数据已被库累积。 许多重要信息隐藏在此类数据后面。 本文的目的是使用命名为关联规则挖掘模型的典型数据挖掘(DM)技术,根据借阅记录找到读者的借用规则,并以个性化的方式推荐其他书柜,以便 提高图书馆数据资源的利用率。

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