改进的关联规则挖掘算法在Web个性化服务中的应用

摘要

This Paper focuses on the Web Log Mining and the association-rules mining algorithm-FP_Growth algorithm. The author puts forward a model on web personal information mining and applies it to the individualized service system in digital library called as "My Library". The system proposes the users' interesting rules of implicit profiling using the association-rules mining algorithm. Then the implicit interesting records are recommended to the users and accomplish the individualized service.%文章重点研究了Web日志挖掘以及关联分析中的关联规则挖掘算法FP_Growth算法,提出了一种改进的关联规则挖掘算法,并将该算法应用于某高校图书馆个性化服务系统My Library的设计过程中,从服务器日志中得到用户感兴趣的隐式模式,并将该隐式兴趣集推荐给用户,从而在一定程度上实现了个性化服务.