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Mar, 2022
一种有效的基于图学习的时间链接预测方法：WSDM Cup 2022 第一名
An Effective Graph Learning based Approach for Temporal Link Prediction: The First Place of WSDM Cup 2022
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Qian Zhao, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Yakun Wang...
TL;DR
介绍了一个名为AntGraph的解决方案来进行时间图中的边的存在概率的学习与预测，并通过性能分析和实验数据表明其优越性，AUC分数为0.666和0.902。
Abstract
temporal link prediction
, as one of the most crucial work in temporal graphs, has attracted lots of attention from the research area. The WSDM Cup 2022 seeks for solutions that predict the existence probabilities of edges within time spans over
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