Publications
k-means++: the advantages of careful seeding
Arthur, D. & Vassilvitskii, S.
, 'SODA '07: Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms', Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, 1027-1035 (2007)
Multi--View Clustering
Bickel, S. & Scheffer, T.
, 'Proceedings of the IEEE International Conference on Data Mining' (2004)
A comparative analysis on the bisecting K-means and the PDDP clustering algorithms.
Savaresi, S. M. & Boley, D.
Intell. Data Anal., 8(4) 345-362 (2004) [pdf]
Wordnet improves text document clustering
Hotho, A.; Staab, S. & Stumme, G.
, 'Proc. SIGIR Semantic Web Workshop', Toronto (2003) [pdf]
Evaluation of hierarchical clustering algorithms for document datasets
Zhao, Y. & Karypis, G.
, 'CIKM '02: Proceedings of the eleventh international conference on Information and knowledge management', ACM Press, New York, NY, USA, [http://doi.acm.org/10.1145/584792.584877], 515-524 (2002)
Text Clustering Based on Good Aggregations
Hotho, A.; Maedche, A. & Staab, S.
, 'ICDM '01: Proceedings of the 2001 IEEE International Conference on Data Mining', IEEE Computer Society, Washington, DC, USA, 607-608 (2001) [pdf]
Constrained K-means Clustering with Background Knowledge.
Wagstaff, K.; Cardie, C.; Rogers, S. & Schrödl, S.
, 'ICML', 577-584 (2001) [pdf]
Extending K-Means Clustering to First-Order Representations
Kirsten, M. & Wrobel, S.
Cussens, J. & Frisch, A. M., ed., 'Inductive Logic Programming, 10th International Conference, ILP 2000, London, UK, July 24-27, 2000, Proceedings', 1866(), Lecture Notes in Computer Science, Springer, 112-129 (2000)
$X$-means: Extending $K$-means with Efficient Estimation of the Number of Clusters
Pelleg, D. & Moore, A.
, 'Proc. 17th International Conf. on Machine Learning', Morgan Kaufmann, San Francisco, CA, 727-734 (2000) [pdf]
A comparison of document clustering techniques
Steinbach, M.; Karypis, G. & Kumar, V.
, 'KDD Workshop on Text Mining' (2000) [pdf]
A Comparison of Document Clustering Techniques
Steinbach, M.; Karypis, G. & Kumar, V.
, 'KDD Workshop on Text Mining' (2000)
Accelerating Exact k -means Algorithms with Geometric Reasoning
Pelleg, D. & Moore, A.
, 'Knowledge Discovery and Data Mining', 277-281 (1999) [pdf]
Refining initial points for K-Means clustering
Bradley, P. S. & Fayyad, U. M.
, 'Proc. 15th International Conf. on Machine Learning', Morgan Kaufmann, San Francisco, CA, 91-99 (1998) [pdf]
Clustering Algorithms
Hartigan, J.
1975, John Wiley and Sons, New York
Some Methods for Classification and Analysis of MultiVariate Observations
MacQueen, J. B.
Cam, L. M. L. & Neyman, J., ed., 'Proc. of the fifth Berkeley Symposium on Mathematical Statistics and Probability', 1(), University of California Press, 281-297 (1967)
ISODATA: A novel method of data analysis and pattern classification
Ball, G. & Hall, D.
1965, Technical report, Stanford Research Institute, Menlo Park
Cluster Analysis of Multivariate Data: Efficiency versus Interpretability of Classification
Forgy, E.
Biometrics, 21(3) 768-769 (1965)