一种基于网页浏览行为的用户兴趣度计算方法

Method of computing for user interest degree based on user's browsing behaviors

用户兴趣度的计算是个性化服务的核心,而用户浏览网页时的行为能反映用户的兴趣。文中着重分析保存页面、收藏页面以及网页浏览速度这三种网页浏览行为,且在此基础上结合用户兴趣衰减因子,提出一种新的基于网页浏览行为的用户兴趣的计算方法,并利用K-means算法将浏览的网页内容聚类成不同主题,最后基于这三种网页浏览行为和用户兴趣衰减因子计算用户主题兴趣度。实验结果表明,提出的用户兴趣度计算方法是有效的。

The calculation of user interest degree is the core of personalized service, and the user＇ s browsing behaviors can reflect the user interest. This paper focuses on the analysis of three user＇ s browsing behaviors which include save page, add to bookmark and the web page browsing speed, and on the basis of user interest attenuation factor, proposed a new calculation method of the user interest based on web page browsing behavior, then uses K-means algorithm cluster browsed web content into different themes; finally, it computes the user theme interest degree based on three behaviors. The experimental result shows that the proposed calculation method of user interest degree is effective.