基于Web的用户-对象二分网络实证分析
Empirical analysis of web-based user-object bipartite networks
摘要：
理解基于Web的用户-对象网络的结构和演化是一项重要的任务，因为它们在当今的电子商务中起着至关重要的作用。这封信报告了对两个大型网站audioscrobbler.com和del.icio.us的实证分析，其中用户分别与音乐组和书签连接。度分布和度的相关性为用户和对象的报告。提出了一个新的指标，命名为协同聚类系数，量化的集群行为的基础上的协同选择。在此基础上，研究了聚类特性和聚类度相关性。我们报告了一些新的现象，很好地描述了网络用户的选择机制，并概述了这些现象的相关性的信息推荐问题。
英文摘要：
Understanding the structure and evolution of web-based user-object networks is a significant task since they play a crucial role in e-commerce nowadays. This Letter reports the empirical analysis on two large-scale web sites, audioscrobbler.com and del.icio.us, where users are connected with music groups and bookmarks, respectively. The degree distributions and degree-degree correlations for both users and objects are reported. We propose a new index, named collaborative clustering coefficient, to quantify the clustering behavior based on the collaborative selection. Accordingly, the clustering properties and clustering-degree correlations are investigated. We report some novel phenomena well characterizing the selection mechanism of web users and outline the relevance of these phenomena to the information recommendation problem.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
