基于关联规则挖掘的个性化智能推荐服务

Intelligent Services of Personalized Recommendation based on Association Rules Mining

1概述 随着WWW上的信息的爆炸性增长,用户的"信息过载"和"资源迷向"问题越来越突出.为了解决用户的信息过载和资源迷向问题,人们发展了许多智能推荐服务系统以及相关技术,帮助用户在WWW上快速定位、检索感兴趣的信息.

This paper proposes an intelligent service method on personalized recommendation.which is based on association rules mining for Internet. To alleviate the phenomena of 'information overload' and 'information bewilderment 'in Internet environment, the overall process can be divided into two components: offline part and online part- In offline, Web mining tasks can execute in the logs of Web service resulting in a user transaction file, and the frequent user transaction patterns are extracted by filtering with thresholds of support again, afterwards, constructing aggregating tree of user sessions. In online, the candidate URLs for recommendation can be determined by matching association rules in the aggregating tree with the current active session for the intelligent services of personalization recommendation- The experiments demonstrate that our approach is applicable and effective.