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Understanding the structure and evolution of web-based user-object bipartite networks is an important task since they play a fundamental role in online information filtering. In this paper, we focus on investigating the patterns of online users' behavior and the effect on recommendation process. Empirical analysis on the e-commercial systems show that users have significant taste diversity and their interests for niche items highly overlap. Additionally, recommendation process are investigateddoi:10.1016/j.physa.2011.09.038 fatcat:ufgklgsyp5fu3hk6zsapetsi6i