Graph clustering refers to clustering of data in the form of graphs. Two distinct forms of clustering can be performed on graph data. Vertex clustering seeks to cluster the nodes of the graph into groups of densely connected regions based on either edge weights or edge distances. The second form of graph clustering treats the graphs as the objects to be clustered and clusters these objects on the basis of similarity. The second approach is often encountered in the context of structured or XML data.
Motivation and Background
Node clustering algorithms: Node clustering algorithms...
- Abello, J., Resende, M. G., & Sudarsky, S. (2002). Massive quasi-clique detection. In Proceedings of the 5th Latin American symposium on theoretical informatics (LATIN) (pp. 598–612). Berlin: Springer.Google Scholar
- Aggarwal, C., Ta, N., Feng, J., Wang, J., & Zaki, M. J. (2007). XProj: A framework for projected structural clustering of XML documents. In KDD conference (pp. 46–55). San Jose, CA.Google Scholar
- Ahuja, R., Orlin, J., & Magnanti, T. (1992). Network flows: Theory, algorithms, and applications. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
- Chawathe, S. S. (1999). Comparing hierachical data in external memory. In Very large data bases conference (pp. 90–101). San Francisco: Morgan Kaufmann.Google Scholar
- Dalamagas, T., Cheng, T., Winkel, K., & Sellis, T. (2005). Clustering XML documents using structural summaries. In Information systems. Elsevier, January 2005.Google Scholar
- Gibson, D., Kumar, R., & Tomkins, A. ( ). Discovering large dense subgraphs in massive graphs. In VLDB conference (pp. 721-732). http://www.vldb2005.org/program/paper/thu/p721-gibson.pdf
- Jain, A., & Dubes, R. (1998). Algorithms for clustering data. Englewood, NJ: Prentice-Hall.Google Scholar
- Lee, M., Hsu, W., Yang, L., & Yang, X. (2002). XClust: Clustering XML schemas for effective integration. In ACM conference on information and knowledge management. http://doi.acm.org/10.1145/584792.584841
- Pei, J., Jiang, D., & Zhang, A. (2005). On mining cross-graph quasi-cliques. In ACM KDD conference. Chicago, IL.Google Scholar
- Rattigan, M., Maier, M., & Jensen, D. (2007). Graph clustering with network structure indices. Proceedings of the International Conference on Machine Learning (783-790). ACM: New York.Google Scholar