Apriori算法在图书推荐服务中的应用与研究

Application and Research of Apriori Algorithm in Library's Book Recommendation Service

数据挖掘是近年来数据库领域研究的热点问题之一。当今数字图书馆个性化服务已成为图书馆服务模式的主流,图书推荐服务是其重点之一。关联规则Apriori算法是数据挖掘的关键技术之一,主要是找出数据库中的所有频繁项集,然后由频繁项集产生关联规则。针对传统的Apriori算法存在的缺陷,利用"分割-整合"的思想改进了Apriori算法。将改进后的Apriori算法应用到图书推荐服务应用模型当中,并进行数据挖掘测试,通过与传统Apriori算法进行对比,改进后的Apriori算法的实际运行效果有明显的改进。

Data mining is one of the research hotspots in database area. At present, digital personalized service has become the main- stream service model of library, and book recommendation is one of important services. Association rules Apriori algorithm is one of the key technologies in data mining, and its idea is find of frequent item sets in database, and produces association rules from the sets. Address shortcomings of Apriori algorithm, and introduce improved Apriori algorithm based on idea of ＂Division-Integrate＂. Then it applies the improved Apriori algorithm to books recommended service application model, and tests using data mining for service. By comparing with the traditional Apriori algorithm, the improved algorithm achieves obvious improvement in actual running.