1. Agrawal, R., Gehrke, J., Gunopulos, D., Raghavan, P., 1998. Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications. Proc. ACM SIGMOD Int. Conf. on Management of Data. Seattle, WA, p.94–105.
2. Ankerst, M., Breunig, M., Kriegel, H.P., Sander, J., 1999. OPTICS: Ordering Points to Identify the Clustering Structure. Proc. ACM SIGMOD Int. Con. Management of Data Mining, p.49–60.
3. Duda, R.O., Hart, P.E., 1973. Pattern Classification and Scene Analysis. John Wiley & Sons, New York.
4. Ester, M., Kriegel, H.P., Sander, J., Xu, X., 1996. A Density-based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. Proc. 2nd Int. Conf. on Knowledge Discovery and Data Mining. AAAI Press, Portland, OR, p.226–231.
5. Fayyad, U.M., Piatetsky-Shapiro, G., Smyth, P., Uthurusamy, R., 1996. Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press.