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所属单位：计算机科学与技术学院/人工智能学院/软件学院

发表刊物：Lect. Notes Inst. Comput. Sci. Soc. Informatics Telecommun. Eng.

摘要：The weak ties are crucial bridges between the tightly coupled node groups in complex networks. Despite of their importance, no existing work has focused on the sign prediction of weak ties. A community preserving sign prediction model is therefore proposed to predict the sign of the weak ties. Nodes are firstly divided into different communities. The weak ties are then detected via the connections of the divided communities. SVM classifier is finally trained and used to predict the sign of weak ties. Experiments held on the real world dataset verify the high prediction performances of our proposed method for weak ties of complex networks. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018.

ISSN号：1867-8211

是否译文：否

发表时间：2018-01-01

合写作者：He, Kangya,袁伟伟

通讯作者：关东海