DBCCOM: Density Based Clustering with Constraints and Obstacle Modeling

Author:

Duhan Neelam,Sharma A. K.

Publisher

Springer Berlin Heidelberg

Reference20 articles.

1. Han, J., Kamber, K.M.: Data Mining: Concepts and Techniques. Morgan Kaufmann, San Francisco (2000)

2. Kaufman, L.: Finding groups in data: An introduction to cluster analysis. Wiley, New York (1990)

3. Karypis, G., Han, E., Kumar, V.: Chameleon: A hierarchical clustering algorithm using dynamic modeling. IEEE Computer, 68–75 (1999)

4. Ester, M., Kriegel, H.-P., Sander, J., Xu, X.: A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. In: Proceedings of 2nd International Conf. on Knowledge Discovery and Data Mining, pp. 226–231. AAAI Press, Portland (1996)

5. Jain, A.K., Dubes, R.C.: Algorithms for Clustering Data. Prentice-Hall, Inc., Englewood Cliffs (1988)

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