Comparative analysis of graph clustering algorithm using bloggers data

Various clustering algorithms utilize novel techniques for clustering data. It is very difficult to decide which algorithms to be used for clustering large graph like PPI networks and various biological networks and hence Comparative analysis provides important insight into application specific usage of corresponding techniques and provides motivation for further studies in the same domain. In this work, the authors investigated some of the criteria through which such comparison can be done for clustering algorithm. For this comparative analysis of two well-known graph clustering algorithm MCL (Markov clustering Algorithm) and GRASP (Greedy Randomized Adaptive Search Procedure) has been done. The experiments based on the real blog data were done for comparisons based on the different parameters for different applications.