Link prediction tasks focus on predicting possible future connections. Most existing researches measure the likelihood of links by different similarity scores node pairs and predict between nodes. However, similarity-based approaches have some challenges in information loss nodes generalization ability indexes. To address above issues, we propose a Line Graph Contrastive Learning (LGCL) method ...

This paper presents a new and efficient algorithm, ILIGRA, for inverse line graph construction. Given a line graph H , ILIGRA constructs its root graph G with the time complexity being linear in the number of nodes in H . If ILIGRA does not know whether the given graph H is a line graph, it firstly assumes that H is a line graph and starts its root graph construction. During the root graph cons...

We prove that if a graph H has the same Tutte polynomial as the line graph of a d-regular, d-edge-connected graph, then H is the line graph of a d-regular graph. Using this result we prove that the line graph of a regular complete t-partite graph is uniquely determined by its Tutte polynomial. We prove the same result for the line graph of any complete bipartite graph.