Arthur, D. & Vassilvitskii, S. (2007), k-means++: the advantages of careful seeding, in 'SODA '07: Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms' , Society for Industrial and Applied Mathematics, Philadelphia, PA, USA , pp. 1027--1035 .

Bickel, S. & Scheffer, T. (2004), Multi--View Clustering, in 'Proceedings of the IEEE International Conference on Data Mining' .

Savaresi, S. M. & Boley, D. (2004), 'A comparative analysis on the bisecting K-means and the PDDP clustering algorithms.', Intell. Data Anal. 8 (4), 345-362.

Hotho, A.; Staab, S. & Stumme, G. (2003), Wordnet improves text document clustering, in 'Proc. SIGIR Semantic Web Workshop' .

Zhao, Y. & Karypis, G. (2002), Evaluation of hierarchical clustering algorithms for document datasets, in 'CIKM '02: Proceedings of the eleventh international conference on Information and knowledge management' , ACM Press, New York, NY, USA , pp. 515--524 .

Hotho, A.; Maedche, A. & Staab, S. (2001), Text Clustering Based on Good Aggregations, in 'ICDM '01: Proceedings of the 2001 IEEE International Conference on Data Mining' , IEEE Computer Society, Washington, DC, USA , pp. 607--608 .

Wagstaff, K.; Cardie, C.; Rogers, S. & Schrödl, S. (2001), Constrained K-means Clustering with Background Knowledge., in 'ICML' , pp. 577-584 .

Kirsten, M. & Wrobel, S. (2000), Extending K-Means Clustering to First-Order Representations, in James Cussens & Alan M. Frisch, ed., 'Inductive Logic Programming, 10th International Conference, ILP 2000, London, UK, July 24-27, 2000, Proceedings' , Springer, , pp. 112-129 .

Pelleg, D. & Moore, A. (2000), $X$-means: Extending $K$-means with Efficient Estimation of the Number of Clusters, in 'Proc. 17th International Conf. on Machine Learning' , Morgan Kaufmann, San Francisco, CA, , pp. 727--734 .

Steinbach, M.; Karypis, G. & Kumar, V. (2000), A comparison of document clustering techniques, in 'KDD Workshop on Text Mining' .

Steinbach, M.; Karypis, G. & Kumar, V. (2000), A Comparison of Document Clustering Techniques, in 'KDD Workshop on Text Mining' .

Pelleg, D. & Moore, A. (1999), Accelerating Exact k -means Algorithms with Geometric Reasoning, in 'Knowledge Discovery and Data Mining' , pp. 277-281 .

Bradley, P. S. & Fayyad, U. M. (1998), Refining initial points for K-Means clustering, in 'Proc. 15th International Conf. on Machine Learning' , Morgan Kaufmann, San Francisco, CA, , pp. 91--99 .

Hartigan, J. (1975), Clustering Algorithms , John Wiley and Sons, New York .

MacQueen, J. B. (1967), Some Methods for Classification and Analysis of MultiVariate Observations, in L. M. Le Cam & J. Neyman, ed., 'Proc. of the fifth Berkeley Symposium on Mathematical Statistics and Probability' , University of California Press, , pp. 281-297 .

Ball, G. & Hall, D. (1965), 'ISODATA: A novel method of data analysis and pattern classification' , Technical report, Stanford Research Institute , Menlo Park .

Forgy, E. (1965), 'Cluster Analysis of Multivariate Data: Efficiency versus Interpretability of Classification', Biometrics 21 (3), 768-769.