Dataset for "Towards Better Evaluation for Dynamic Link Prediction"

These are the datasets used in <em>Towards Better Evaluation for Dynamic Link Prediction</em> For preparing the datasets, we closely follow the baseline methods' data preparation strategy.<br> The original networks are saved as &lt;network&gt;.csv. The networks are formatted as follows:<br> * Each edge is denoted in one line.<br> * Each line has the following format: source_node, destination_node, timestamp, edge_label, comma-separated arrays of edge features.<br> * Please note that if there is no edge label available, the edge_label column will be filled with 0s only for loading purpose; these labels are not used in the link prediction task.<br> * The first line denotes the network format.<br> * Edge features should include at least one feature. If there is no edge feature available, a 0 value is used for all the edges. The network edge-lists are pre-processed for different methods to use them (Specifically, for preprocessing the data, we use the scripts available in "preprocess_data.py" file of the corresponding baseline).<br> Ater preprocessing the network edge-list, there are three files that are used by the models:<br> * &lt;ml_network&gt;.csv: this file contains the timestamp edge-list.<br> * &lt;ml_network&gt;.npy: this file contains the edge features in the dense `npy` format that has the features in binary format.<br> * &lt;ml_network_node&gt;.npy: this file contains the node features in the dense `npy` format that contains the node features in binary format.<br> Please note that when the edge features or node features are absent, we use a vector of zeros is used as the node/edge features in line with the baseline methods.