Maximum Common Subgraph and Median Graph Computation from Graph Representations of Web Documents Using Backtracking Search
After constructing graph representations for a set of web documents, there are several techniques to determine the similarity between same-type objects. This is achieved by graph matching. The measure of similarity may be based on the size of the maximum common subgraph. In this paper, the authors are interested in the problem of Maximum Common Subgraph (MCS) and median graph computation for the purpose of graph clustering using backtracking search. Median of a graph helps in the extension of prevalent term frequency based clustering algorithms to graph based clustering.