Before revision:  Graph similarity computation for metrics such as Graph Edit Distance (GED) is typically NP-hard , and existing heuristics-based algorithms usually achieves a unsatisfactory trade-off between accuracy and efficiency.
After revision:  Graph similarity computation for metrics such as Graph Edit Distance (GED) is important in many real-world applications, such as 3D action recognition and biological molecular identification. Computing exact GED values is typically an NP-hard , and existing heuristics-based algorithms usually achieves a unsatisfactory trade-off between accuracy and efficiency.