BICE: Exploring Compact Search Space by Using Bipartite Matching and Cell-Wide Verification

Subgraph matching is the problem of searching for all embeddings of a query graph in a data graph, and subgraph query processing (also known as subgraph search) is to find all the data graphs that contain a query graph as subgraphs. Extensive research has been done to develop practical solutions for both problems. However, the existing solutions still show limited query processing time due to a lot of unnecessary computations in search. In this paper, we focus on exploring as compact search space as possible by using three techniques: (1) pruning by bipartite matching, (2) pruning by failing sets with bipartite matching, and (3) cell-wide verification. We propose a new algorithm BICE, which combines these three techniques. We conduct extensive experiments on real-world datasets as well as synthetic datasets to evaluate the effectiveness of the techniques. Experiments show that our approach outperforms the fastest existing subgraph search algorithm by up to two orders of magnitude in terms of elapsed time to process a query. Our approach also outperforms state-of-the-art subgraph matching algorithms by up to two orders of magnitude.