Multi-features link prediction based on matrix

Existing link prediction methods have mostly adopted overlay network to represent social network and used topological features or attributive features between two nodes to predict the formation of links. However, the limitation of these methods is that they not only use a single feature for link prediction, but also not take into account the time factor and the importance of features. This paper considered the problem of temporal link prediction on the basis of using various features at the same time. Specifically, it presented a matrix-based method for combining temporal features, weighted attributive features and weighted topological features. Using two different datasets our experiments have confirmed that our approach achieved better performance.