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

Abstract

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 Abstr(3) cell-wide verifica- tion. We propose a new algorithm Bid, hich combines these three techniques. We conduct extensive periments on real-world datasets as well as synthetic datasets to evaluate the effectiveness of the techniques. Experiments show that our approach outper- forms 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.