An Approach to Finding Similarity Between Two Community Graphs Using Graph Mining Techniques

Graph similarity has studied in the fields of shape retrieval, object recognition, face recognition and many more areas. Sometimes it is important to compare two community graphs for similarity which makes easier for mining the reliable knowledge from a large community graph. Once the similarity is done then, the necessary mining of knowledge can be extracted from only one community graph rather than both which leads saving of time. This paper proposes an algorithm for similarity check of two community graphs using graph mining techniques. Since a large community graph is difficult to visualize, so compression is essential. This proposed method seems to be easier and faster while checking for similarity between two community graphs since the comparison is between the two compressed community graphs rather than the actual large community graphs.

@article{Rao2016,
  title     = {An Approach to Finding Similarity Between Two Community Graphs Using Graph Mining Techniques},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {5},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Bapuji Rao and Saroja Nanda Mishra},
  doi       = {10.14569/IJACSA.2016.070563},
  url       = {https://doi.org/10.14569/IJACSA.2016.070563}
}