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A Study on Link Prediction Algorithm Based on Users’ Privacy Information in the Weighted Social Network

机译:基于用户隐私信息在加权社交网络中的链路预测算法研究

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With the rapid development of information technology, more and more people join in social network. People are willing to share their information in the network to develop their contacts. Social network is reflection of real social relations. Many scholars have shown keen interest in this field. Link Prediction Algorithm is one of the important research direction. Interaction between users and the privacy information existing among individual users greatly affects the accuracy of link prediction. This paper firstly does network weighted processing by using some interactive behavior characteristics of social network users. Then through considering the user’s privacy information and analyzing the users’ interest preference, the paper provides a weighted directed network link prediction algorithm. Finally, the simulation experiment shows that this algorithm has high prediction accuracy.
机译:随着信息技术的快速发展,越来越多的人加入社交网络。人们愿意在网络中分享他们的信息以发展他们的联系人。社交网络是真正的社会关系的反映。许多学者都表现出对此字段的敏锐兴趣。链路预测算法是重要的研究方向之一。用户之间存在的互动和个人用户之间存在的隐私信息极大地影响链路预测的准确性。本文首先使用社交网络用户的一些互动行为特征进行网络加权处理。然后通过考虑用户的隐私信息并分析用户的兴趣偏好,该文件提供了一种加权定向网络链路预测算法。最后,仿真实验表明该算法具有高预测精度。

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