自动分层推荐算法

AUTOMATIC LAYERED RECOMMENDATION ALGORITHM

推荐是Web个性化服务的核心。提出一种自动分层推荐算法 ,利用页面分层自动选择最佳的匹配粒度 ,进行基于频繁导航路径的推荐。实验结果表明 ,该算法大大减少了在线匹配的开销 ,可以成功地应用到Web日志挖掘中。

Recommendation is the kernel of Web personalization. In this article, we propose an automatic layered recommendation algorithm, which uses page layering to automatically choose the optimal matching granularity and to make recommendation based on frequent navigation paths. The experimental results show that it greatly reduces online cost, and can be successfully applied to Web log mining.