Simulation-based Approximate Graph Pattern Matching
Xiaoshuang Chen · 2020
Graph pattern matching is a fundamental problem in analyzing attributed graphs, that is to search the matches of a given query graph in a large data graph. However, existing algorithms either encounter with the performance issues or cannot capture reasonable matches. In this paper, we propose a simulation-based approximate pattern matching algorithm that is not only efficient to compute, but also able to capture those reasonable matches (missed by existing algorithms)