Abstract
In previous link prediction researches, most scholars evaluate the influence of endpoints by the degree or H-index of endpoints, resulting in limited prediction accuracy. Through abundant investigations, we can evaluate the influence of endpoints accurately by the hybrid influence of neighbor nodes. Meanwhile, we calculate the hybrid influence of neighbors (HIN) by the average values of degree and H-index. In the paper, we conceive a HIN model. Large-scale experiments on 12 real datasets indicate that the conceived methods can significantly enhance the accuracy of link prediction.
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