论文标题
多重社交网络中的新位置免费链接预测
A Novel Location Free Link Prediction in Multiplex Social Networks
论文作者
论文摘要
近几十年来，社交网络的出现使互联网服务提供商（例如Facebook，Twitter和Uber）能够取得巨大的商业成功。链接预测被认为是建立社交网络拓扑并保持它们不断发展的常见实践。通常，链接预测方法取决于用户的位置信息，这些信息不时遭受信息泄漏。为了解决这个问题，智能设备公司（例如Apple Inc.）不断收紧其隐私政策，阻止互联网服务提供商获取位置信息。因此，设计位置免费链接预测方法非常重要，而准确性仍然保留。在这项研究中，为复杂的社交网络提出了一种新的位置免费链接预测方法。实际数据集上的实验表明，我们位置免费链接预测方法的精度增加了10％。
In recent decades, the emergence of social networks has enabled internet service providers (e.g., Facebook, Twitter and Uber) to achieve great commercial success. Link prediction is recognized as a common practice to build the topology of social networks and keep them evolving. Conventionally, link prediction methods are dependent of location information of users, which suffers from information leakage from time to time. To deal with this problem, companies of smart devices (e.g., Apple Inc.) keeps tightening their privacy policy, impeding internet service providers from acquiring location information. Therefore, it is of great importance to design location free link prediction methods, while the accuracy still preserves. In this study, a novel location free link prediction method is proposed for complex social networks. Experiments on real datasets show that the precision of our location free link prediction method increases by 10 percent.
