In this article, the phenomenon of scientist cooperation in the scientist cooperation network is studied from the perspectives of information spread and link prediction. By mining the information in the scientist cooperation network, analyzing the cooperation has been generated and discovering potential cooperation opportunities. It helps to build a richer cooperation network with more content. Information spread can reflect the inner laws of network structure formation, and the link prediction method can retain the integrity of network information to the maximum extent. First, the real network is abstracted by analyzing its structure as well as node attributes into a simulated network. Second, the process of information spread in the cooperation network is simulated by improving the traditional SIS model. Some improvements are made to the link prediction algorithm for the impact brought to the network by information spread. Finally, the experimental results in the scientist cooperation network show that the hybrid weighted link prediction algorithm combining node attributes and spread factors can improve the accuracy of link prediction and provide suggestions for scientists to find partners. The comparative experiments on simulated and real networks not only validate the effectiveness of the propagation model in the scientist cooperation network, but also verify the accuracy of the hybrid weighted link prediction algorithm.

中文翻译：

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确定科学家之间的潜在合作关系

本文从信息传播和链接预测的角度研究科学家合作网络中的科学家合作现象。通过挖掘科学家合作网络中的信息，分析已经产生的合作，发现潜在的合作机会。有助于构建内容更丰富、内容更丰富的合作网络。信息传播可以反映网络结构形成的内在规律，链路预测方法可以最大程度地保留网络信息的完整性。首先，通过分析真实网络的结构和节点属性将真实网络抽象成模拟网络。其次，通过改进传统的SIS模型，模拟合作网络中的信息传播过程。针对信息传播给网络带来的影响，对链路预测算法进行了一些改进。最后，科学家合作网络中的实验结果表明，结合节点属性和扩散因子的混合加权链路预测算法可以提高链路预测的准确性，为科学家寻找合作伙伴提供建议。仿真网络与真实网络的对比实验不仅验证了传播模型在科学家合作网络中的有效性，也验证了混合加权链路预测算法的准确性。在科学家合作网络中的实验结果表明，结合节点属性和扩散因子的混合加权链路预测算法可以提高链路预测的准确性，为科学家寻找合作伙伴提供建议。仿真网络与真实网络的对比实验不仅验证了传播模型在科学家合作网络中的有效性，也验证了混合加权链路预测算法的准确性。在科学家合作网络中的实验结果表明，结合节点属性和扩散因子的混合加权链路预测算法可以提高链路预测的准确性，为科学家寻找合作伙伴提供建议。仿真网络与真实网络的对比实验不仅验证了传播模型在科学家合作网络中的有效性，也验证了混合加权链路预测算法的准确性。