Edge embedding is a technique in graph representation learning that focuses on encoding the relationships between nodes as vectors, offering a way to capture and utilize the rich information inherent in the connections of a graph. This approach is crucial for tasks like link prediction, edge classification, and network reconstruction, where understanding the nature and strength of interactions is essential.
