强关联规则挖掘在智慧图书馆个性化推送服务中的应用研究

Applied Research on Strong Association Rules in Personalized Information Push Service of Smart Library

【目的/意义】关联数据发现与个性化信息推送是未来智慧图书馆建设的核心内容。大数据环境下,为了提高图书馆推送信息的精准度,本文把适合个性化信息推送服务的强关联规则挖掘技术引入到高校图书馆智慧化信息服务中,研究在图书馆集成管理系统的基础上实现图书的智能查询和个性化信息推送。【方法/过程】在具体的研究中,由于经典关联规则挖掘需要多次扫描数据库,生成大量的冗余关联规则信息,因此需要重新定义领域内强关联规则和频繁项目集,提出处理海量数据需要的强关联规则算法。【结果/结论】将改进的算法应用到图书借阅和信息查询数据的分析中,以减少图书频繁项集的产生,避免冗余规则的挖掘和生成,从而实现关联图书信息的高效挖掘和个性化推送。

【Purpose/significance】Data discovery and personalized push service are the important content of Smart Library construction in the future. In order to improve the accuracy of Library push information in the big data environment, this paper introduces the strong association rule mining technology into the information service of university library, which is suitable for personalized information push service.【Method/process】In practice, because of the mining of classical association rules, it is necessary to scan the database many times and generate a large amount of redundant association rules information. Therefore, it is necessary to redefine strong association rules and frequent itemsets in the domain, and propose a strong association rule algorithm for dealing with massive data.【Result/conclusion】The analysis of improved algorithm is applied to the library of historical data to reduce the frequent items mining, avoid generating redundant rules,and achieve efficient mining and personalized information push related books.