Before revision:  With window sizes of 3 to 4 time steps, GNNs achieve at least 95\% accuracy compared to using the entire timeline of the graph . With window sizes of 6 or 8, at least 99\% accuracy could be retained. These discoveries have direct consequences for training GNNs over temporal graphs. We provide the code URL and the newly compiled datasets URL for reproducibility and reuse .
After revision:  With window sizes of 3 to 4 time steps, GNNs achieve at least 95\% accuracy compared to using the entire timeline of the graph data. Furthermore, our experiments confirm that implicit knowledge becomes more important when fewer explicit knowledge is available .