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Prediction of Links and Weights in Networks by Reliable Routes

机译:用可靠的路由预测网络中的链路和权重

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摘要

Link prediction aims to uncover missing links or predict the emergence of future relationships from the current network structure. Plenty of algorithms have been developed for link prediction in unweighted networks, but only a few have been extended to weighted networks. In this paper, we present what we call a “reliable-route method” to extend unweighted local similarity indices to weighted ones. Using these indices, we can predict both the existence of links and their weights. Experiments on various real-world networks suggest that our reliable-route weighted resource-allocation index performs noticeably better than others with respect to weight prediction. For existence prediction it is either the highest or very close to the highest. Further analysis shows a strong positive correlation between the clustering coefficient and prediction accuracy. Finally, we apply our method to the prediction of missing protein-protein interactions and their confidence scores from known PPI networks. Once again, our reliable-route method shows the highest accuracy.
机译:链接预测旨在发现丢失的链接或根据当前网络结构预测未来关系的出现。已经开发了许多算法用于未加权网络中的链路预测,但是只有少数算法扩展到了加权网络。在本文中,我们提出了所谓的“可靠路由方法”,以将未加权的局部相似性指标扩展到加权的相似性指标。使用这些索引,我们可以预测链接的存在及其权重。在各种实际网络上进行的实验表明,就权重预测而言,我们的可靠路由加权资源分配索引的性能明显优于其他路由。对于存在预测,它是最高的,或者非常接近最高。进一步分析表明,聚类系数与预测精度之间存在很强的正相关性。最后,我们将我们的方法应用于从已知的PPI网络预测缺失的蛋白质-蛋白质相互作用及其置信度得分。我们的可靠布线方法再次显示出最高的准确性。

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