Pattern Recognition Using Graph Edit Distance

Abstract

Graph edit distance is one of the most crucial techniques to measure the similarity between two graphs. Graph edit distance is defined as the minimum number of modifications in terms of edit operations required to transform one graph into another. The significant applications of graph edit distance include error-tolerant graph matching in structural pattern recognition. This chapter describes the principal techniques and algorithm to find the graph edit distance. We also present recent advances in computing graph edit distance and its implications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.