MODULAR IDENTIFICATION OF FREQUENT SUB GRAPH STRUCTURES IN STRUCTURED GRAPH DOMAIN USING GRAPH MINING TECHNIQUE

The Frequent Subgraph search plays a vital role to study structured graph with different level of implications. Our conventional setup initially focuses with subgraph and its vertex-edge connectivity. This paper perform a detailed study of classified subgraph of different sub structure towards variant vertex clusters in the field of graph mining which can be carried out with the comparison search prediction strategies. We will implement our frequent sub graph identification techniques with the implementation of Mathematical Computation based edge cluster domains related to its frequency of occurrence. We will also perform survey analysis strategies for the successful implementation of our proposed research technique in several sampling domains with a maximum level of improvements. In near future we will implement the Identification of Frequent Sub structure graph mining techniques for predicting the Graph sub structure behaviors.