Ertöz L., Steinbach M., Kumar V. (2003). Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data.. SIAM International Conference on Data Mining (SDM '03). 

Ester M., Kriegel H.-P., Sander J., and Xu X. (1996). A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. In Proc. 2nd Int. Conf. on Knowledge Discovery and Data Mining (KDD'96 ). AAAI Press, Menlo Park, CA, pp. 226-231 Ester M., Kriegel H.-P., Sander J., Wimmer M., Xu X. (1998). Incremental Clustering for Mining in a Data Warehous-ing Environment. VLDB 1998: 323-333 Gaber M., Zaslavsky A. and Krishnaswamy S. (2005). Mining Data Streams: A Review. SIGMOD 
Record, 34(2). 

Gao J., Li J., Zhang Z., Tan P.-N. (2005). An Incremental Data Stream Clustering Algorithm Based on Dense Units Detection. Proc. PAKDD'05, pp. 420-425. 

Guénoche A. (2004). Clustering by vertex density in a Graph. Meeting of the International Federation of the Classifica-tion Societies. Chicago, Classification, Clustering and Data Mining, D. Banks et al. (Eds.), Springer, 15-23. 

Hader S., Hamprecht F. A. (2003). Efficient density clustering using basin spanning trees. Between Data Science and Applied Data Analysis, 39-48, Springer Journées Graphes Réseaux Modélisation 2004 : http://www.liafa.jussieu.fr/~grm/journees/
Lebart L., Morineau A., Tabard N. (1982) Techniques de la description statistique, Dunod, Paris Lelu A., (1994), Clusters and factors: neural algorithms for a novel representation of huge and highly multidimensional data sets, in E. Diday, Y. Lechevallier & al. eds., New Approaches in Classification and Data Analysis, p. 241-248, Springer-Verlag, Berlin, Lelu A. (2003), Evaluation de trois mesures de similarité utilisées en sciences de l'information. 

Information Sciences for Decision Making, H. Rostaing ed., N°6, 2003. 

Lelu A. François C. (2003), Un algorithme de détection de maxima de densité basé sur la distance distributionnelle: application à la classification optimale fine d'un corpus documentaire, 10èmes Rencontres SFC, Dodge Y., Melfi G. eds., Pr. Acad. Neufchâtel. 

Mitton N., Busson A., Fleury E. (2004) Self-organization in large scale ad hoc networks. The Third Annual Mediterra-nean Ad Hoc Networking Workshop, (MED-HOC-NET 04). Bodrum, Turkey. 

Moody J. (2001) - Identifying dense clusters in large networks, Social Networks, vol. 23, pp. 261-283 Simovici D., Singla N., Kuperberg M. (2004) Metric Incremental Clustering of Nominal Data. 

Proceedings of ICDM 2004, Brighton, UK, pp. 523-527 Saint-Léger M. (1997) Modélisation des flux d'information scientifique et technique par le bruit. 

Thèse CNAM - CERESI, Paris Trémolières R.C. (1979). The percolation method for an efficient grouping of data. Pattern Recognition, 11(4). 

Trémolières R.C. (1994). Percolation and multimodal data structuring - New Approaches in Classification and Data Analysis, Diday E. et al. (eds.), 263-268, Springer Verlag, Berlin. 