中文摘要：

用户对web网页的访问是由用户需求行为确定的一个随着时间演化的复杂双模式二分网络。通过对网站聚类生成的二分网络的实证研究表明，其入度分布呈现出典型的无标度特征和集聚现象，幂指数介于1．7到1．8之间。将这种双模式二分网络映射为两种含权单模式网络：用户群体兴趣广义关联网络和网站资源广义关联网络，从而深入研究用户群体行为的关联性和从用户行为角度网站资源的关联性。实证分析其统计特性表明，两者的边权分布是幂律的，网络节点关联紧密且呈现簇聚特征。用户行为的无标度特征和集聚特点对优化Internet网络拓扑结构，改善其网络性能具有重要意义。

英文摘要：

The Web-visited bipartite networks, called the user interested networks, display a natural bipartite structure： two kinds of nodes coexist with links only between nodes of different kinds. The Web-visited bipartite networks are constructed dynamically in time series by user requirement behaviors, and the characteristic of user requirement collective behaviors can be analyzed through the bipartite networks. The empirical study of the bipartite networks express that the visiting frequency and in-degree distribution are power-law, which the exponential is between 1.7 and 1.8, and the networks have a clustering characteristics. The bipartite networks can be projected to two kinds of affiliation unipartite networks dividedly from the Web nodes and user nodes, and produce the collective interesting affiliation networks and Web resource affiliation net-works. The empirical results express that the edge weight distribution of the unipartite affiliation networks is power-law, and the nodes relations are tightness and clustering. The scale-free and clustering characteristics are important to optimize resource distribution and improve the topology structure and performances of Internet.