Subgraph Matching

Subgraph matching, the task of identifying a smaller graph (query) within a larger graph (target), is a computationally challenging problem with broad applications across diverse fields. Current research focuses on developing more efficient and accurate algorithms, including neural network-based approaches like graph neural networks (GNNs) and reinforcement learning methods, often incorporating techniques to improve explainability and robustness to noise or outliers. These advancements are crucial for improving the scalability and reliability of graph-based analyses in areas such as knowledge graph completion, bioinformatics, and database systems.