通过基于递归子图的排序预测链接方向
Predicting link directions via a recursive subgraph-based ranking
摘要：
链接方向对网络的功能至关重要，它们的预测有助于从不完整的真实世界数据中更好地了解有向网络。研究了利用剩余环的存在性和方向来预测剩余环的方向的问题。我们提出了一个解决方案，首先排名节点在一个特定的顺序，然后预测每个链接从一个排名较低的节点向一个排名较高的。所提出的排名方法递归地工作，通过利用多个尺度上的本地指标，每个指标对应于从原始网络中提取的子图。在真实网络上的实验表明，我们的方法可以正确地恢复相当一部分链接的方向，这优于纯粹的本地或全球的方法。
英文摘要：
Link directions are essential to the functionality of networks and their prediction is helpful towards a better knowledge of directed networks from incomplete real-world data. We study the problem of predicting the directions of some links by using the existence and directions of the rest of links. We propose a solution by first ranking nodes in a specific order and then predicting each link as stemming from a lower-ranked node towards a higher-ranked one. The proposed ranking method works recursively by utilizing local indicators on multiple scales, each corresponding to a subgraph extracted from the original network. Experiments on real networks show that the directions of a substantial fraction of links can be correctly recovered by our method, which outperforms either purely local or global methods.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
