Subgraph Isomorphism

Subgraph isomorphism focuses on efficiently determining whether a smaller graph (subgraph) exists within a larger graph, and potentially counting all occurrences. Current research emphasizes leveraging machine learning, particularly graph neural networks (GNNs) with novel message-passing schemes (e.g., edge-centric approaches) and incorporating techniques like Monte Carlo tree search to improve approximation algorithms. These advancements aim to address the inherent computational complexity of the problem, impacting diverse fields by enabling more efficient analysis of complex relational data in areas such as cheminformatics, social network analysis, and image recognition.