Entropy-based link prediction in weighted networks |
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Institution: | 1. Department of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China;2. Department of Industrial and Systems Engineering, University of Florida, Gainesville 32611, USA |
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Abstract: | Information entropy has been proved to be an effective tool to quantify the structural importance of complex networks.In a previous work Xu et al. Physica A, 456 294(2016)], we measure the contribution of a path in link prediction with information entropy. In this paper, we further quantify the contribution of a path with both path entropy and path weight,and propose a weighted prediction index based on the contributions of paths, namely weighted path entropy(WPE), to improve the prediction accuracy in weighted networks. Empirical experiments on six weighted real-world networks show that WPE achieves higher prediction accuracy than three other typical weighted indices. |
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Keywords: | link prediction weighted networks information entropy |
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