改进的关联规则算法在电子商务中的应用

Web日志数据中保存有大量用户访问信息,而Web日志挖掘就是对系统日志信息以及用户的注册数据等进行挖掘,以发现有用的模式和知识。首先介绍了Web日志挖掘的基本流程,然后介绍了电子商务中的日志挖掘,并着重分析了在模式识别中如何利用改进的关联规则算法来挖掘出用户频繁访问的路径和页面兴趣度,为个性化推荐系统模型提供了依据,从而证实了对Web日志数据进行挖掘具有很重要的现实意义。

The Application of Improvement Association Rules Algorithm in E-Commerce

A large number of users accessing information are saved in Web log data,and Web Log Mining is used to discover useful patterns and knowledge from the system log information and the registration data of the users.This paper first introduces the basic flow of Web log mining,then emphasized to analyze how make use of the the improvement association rules algorithm to find the frequent access path and rate of page interest and provided the basis for the characteristic recommendation system model,Thus confirmed carrying on the excavation to the Web log data has the very important and realistic meaning.