中文摘要：

在移动环境下让用户对博客进行直接评分有很多弊端。因此,如何获取用户对博客的评分信息已成为一个亟待解决的问题。基于隐性评分技术,通过分析用户阅读博客时的阅读速度和阅读文章的比例,计算出用户对博客的偏好信息,进而将传统的基于项目的协同过滤技术应用到博客推荐中,提出了移动环境下基于隐性评分的协同过滤博客推荐技术。最后,通过实验证明该技术可以在移动环境下有效地为用户推荐符合其兴趣的博客。

英文摘要：

In the mobile environment,the traditional explicit rating method is not feasible.Therefore,how to acquire the rating scores that users put on the web logs has become an urgent interesting issue.This paper proposes an implicit rating technology based on the time users spend on the web logs and the percentage users have read the web logs.Based on it,the traditional item-based collaborative filtering technology is applied to the blog recommendation.Finally,results of the experiments conducted demonstrate that the technology proposed can effectively recommend the mobile users suitable blogs that they are interested in.