1. Han, J.W., Kamber, M.: Data Mining Concepts and Techniques. Mogran Kaufmann Publishers, 2001. 335
2. Macqueen, J.: Some methods for classification and analysis of multivariate observations. In: LeCam, L. M. and Neyman, J. (eds.): Proceedings of the 5th Berkeley Symposium on Mathematics and Statistics, Berkeley: University of California Press, 1967. 281-297.
3. Zhang, T., Ramakrishnan, R., and Livny, M.: BIRCH: An effective data clustering method for very large database. In Proceedings of the 1996 ACM-SIGMOD conference International Conference on Management of Data, Montreal, Canada, 1996. 103-114.
4. Ester, M., Kriegel, H. P. and Sander, J.: Spatial data mining: A database approach. In Proceedings of Symposium on Large Spatial Databases (SSD’97), Berlin, Germany, July 1997. 47-66.
5. Xia, H.X. et al.: Ant-based text clustering using semantic similarity measure: progress report and first stage experiment. In: Gu, J.F. and Chroust, G. (eds.): Proceedings of the First World Congress of the International Federation for Systems Research, Kobe, Japan, 2005. 428