Abstract
In recent years, online social networks have undergone a significant growth and attracted much attention. In these online social networks, link prediction is a critical task that not only offers insights into the factors behind creation of individual social relationship but also plays an essential role in the whole network growth. In this paper, we propose a novel link prediction method based on hypergraph. In contrast with conventional methods that using ordinary graph, we model the social network as a hypergraph, which can fully capture all types of objects and either the pair wise or high-order relations among these objects in the network. Then the link prediction task is formulated as a ranking problem on this hypergraph. Experimental results on Sina-Weibo dataset have demonstrated the effectiveness of our methods.
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