Depending on the underlying graph, you also need to handle cycles intelligently. In social networks, mutual relationships are ...

Abstract: Triangle classification is essential in graph analysis, such as for effectively detecting communities, evaluating clusters, and quantifying connection density. While traditional algorithms ...

Abstract: The great success of graph neural networks (GNNs) in graph-structured data tasks benefits from the powerful structure learning abilities of their architectures. For complex datasets, too ...