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 temporal graph. This paper introduces the solution of AntGraph, which wins the 1st place in the competition. We first analysis the theoretical upper-bound of the performance by removing temporal information, which implies that only structure and attribute information on the graph could achieve great performance. Based on this hypothesis, then we introduce several well-designed features. Finally, experiments conducted on the competition datasets show the superiority of our proposal, which achieved AUC score of 0.666 on dataset A and 0.902 on dataset B, the ablation studies also prove the efficiency of each feature. Code is publicly available at https://github.com/im0qianqian/WSDM2022TGP-AntGraph.

翻译：时间链接预测是时间图中最重要的工作之一,它吸引了研究领域的很多关注。WSDM Cup 2022 寻求预测时间图上时间边缘概率的解决方案。本文介绍了在竞争中赢得第一位的AntGraph的解决方案。我们首先通过删除时间信息来分析理论上的高级性能,这意味着只有图上的结构和属性信息才能取得显著的性能。根据这一假设,我们随后引入了几个设计良好的特征。最后,在竞争数据集上进行的实验显示了我们提案的优势,在数据集A和数据集B上实现了0.666和0.902的ACE分,反动研究也证明了每种特性的效率。守则可在https://github.com/im0qian/WSDD2022TGP-AntGraph上公开查阅。