基于用户访问兴趣的Web站点路径聚类研究

用户对Web站点的访问代表了用户对Web站点上页面的访问兴趣。这种兴趣程度可以通过用户对Web站点上页面的浏览顺序表现出来。Web站点的访问日志记录了用户访问页面的详细信息。在对Web站点的访问日志进行事务识别后,按照访问兴趣对群体用户对Web站点的访问顺序进行聚类分析,则每一个聚类集反映出该聚类集中的全体用户具有相似的访问兴趣。文中在用户访问兴趣度量中综合考虑用户访问路径、网页内容、在此页面的驻留时间、此页面浏览频度因素,提出了一种基于用户访问兴趣的路径聚类算法。最后通过实验来验证这种算法的有效性。

Research on path clustering in web sites based on the access interest of users

When users access a Web site, the access of the users represents the interest of users in the Web pages of the Web site. Each user＇ s interest can be manifested by the sequence of each user access. Web log files detailedly record the access information. After processing the Log in the Web site and identifying each user access transaction, the access paths of all the users can be clustered according to the interest of the users. Then each cluster can represent the similar access interest of the users in the cluster. The access path of users, the page content, the staying period of at the page and the frequency of each user access are taken into account in measurement of browsing interest in this paper, and a path clustering algorithm based on users access interest is proposed. The experimental result shows that this algorithm is effective.