An approach to detect sub-community graph in n-community graphs using graph mining techniques

Finding of frequent sub-graphs is an important operation on graphs and it is defined as detection of all sub-graphs that appear frequently in a set of graphs. This paper proposes detection of frequent sub-community graph from n-set of community graph of villages; are useful for characterizing community graph sets, finding difference among groups of community graphs, classifying and clustering of community graphs, and building community graph indices leading to knowledge extraction. The given n-community graphs of villages and the sub-community graph, which is to be detected are first represented as adjacency matrices. Then the sub-community graph adjacency matrix is compared with the n-community graph's adjacency matrices sequentially. The paper concludes with analysis of the proposed algorithm using graph mining techniques with supportive example, satisfactory results and screenshots.