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Method of user modeling based on overlapping communities detection

机译:基于重叠社区检测的用户建模方法

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With the development of social networks, it is important to building the user model which can reflects users' interests. However traditional methods of user modeling aren't well detect users' interests. We review the traditional user modeling method, then presented an idea, it's that the interest of user in social networks is overlapping of multi-community' interest. Based on this idea, overlapping communities detection algorithm (OCD) is introduced into user modeling, a user modeling method based on overlapping communities detection algorithm is presented, and used it in personal recommendation. Experimental results show that this method can effectively reduce the prediction errors of collaborative filtering algorithms based on the user.
机译:随着社交网络的发展,建立能够反映用户兴趣的用户模型非常重要。但是,传统的用户建模方法不能很好地检测用户的兴趣。我们回顾了传统的用户建模方法,然后提出了一个想法,即用户对社交网络的兴趣与多社区的兴趣重叠。基于此思想,将重叠社区检测算法(OCD)引入用户建模中,提出了一种基于重叠社区检测算法的用户建模方法,并将其用于个人推荐中。实验结果表明,该方法可以有效地减少基于用户的协同过滤算法的预测误差。

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