Fast and Exact Subgraph Isomorphism Querying: Using Embedding and Searching Techniques
Zihao Li, Jiazhen Xu, Baoyi He, Klaus‐Dieter Schewe · 2022
Subgraph isomorphism querying finds if there is any instance of a given pattern within the data graph, and has a wide applications in all fields related to graphs, such as databases, social network analysis, chemistry and biology. It is well-known that this task can be done by brute-force, but the complexity increases exponentially with the graph size and is proven an NP-hard problem. Many works have been done on accelerating subgraph isomorphism with the sacrifice of accuracy, most of which still suffer from the inherent difficulty, especially when the graph size get large. In this paper we propose a novel method, named SubQHS (Subgraph Querying based on Heuristic Search), which can quickly find an existing pattern in the data graph using heuristic. We also propose its variant SubQHS-T, which is guaranteed to terminate in polynomial time to get an approximate result.