Conference articles

k-means++: the advantages of careful seeding.
In: SODA '07: Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, pages 1027-1035. Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, 2007.
David Arthur and Sergei Vassilvitskii.
[BibTeX] 
Multi-View Clustering.
In: Proceedings of the IEEE International Conference on Data Mining. 2004.
S. Bickel and T. Scheffer.
[BibTeX] 

Journal articles

A comparative analysis on the bisecting K-means and the PDDP clustering algorithms..
Intell. Data Anal., 8(4):345-362, 2004.
Sergio M. Savaresi and Daniel Boley.
[doi]  [BibTeX] 

Conference articles

Wordnet improves text document clustering.
In: Proc. SIGIR Semantic Web Workshop. Toronto, 2003.
A Hotho, S. Staab and G. Stumme.
[doi]  [BibTeX] 
Evaluation of hierarchical clustering algorithms for document datasets.
In: CIKM '02: Proceedings of the eleventh international conference on Information and knowledge management, pages 515-524. ACM Press, New York, NY, USA, 2002.
Ying Zhao and George Karypis.
[BibTeX] 
Text Clustering Based on Good Aggregations.
In: ICDM '01: Proceedings of the 2001 IEEE International Conference on Data Mining, pages 607-608. IEEE Computer Society, Washington, DC, USA, 2001.
Andreas Hotho, Alexander Maedche and Steffen Staab.
[doi]  [BibTeX] 
Constrained K-means Clustering with Background Knowledge..
In: ICML, pages 577-584. 2001.
Kiri Wagstaff, Claire Cardie, Seth Rogers and Stefan Schrödl.
[doi]  [BibTeX] 
Extending K-Means Clustering to First-Order Representations.
In: J. Cussens and A. M. Frisch, editors, Inductive Logic Programming, 10th International Conference, ILP 2000, London, UK, July 24-27, 2000, Proceedings, volume 1866, series Lecture Notes in Computer Science, pages 112-129. Springer, 2000.
Mathias Kirsten and Stefan Wrobel.
[BibTeX] 
$X$-means: Extending $K$-means with Efficient Estimation of the Number of Clusters.
In: Proc. 17th International Conf. on Machine Learning, pages 727-734. Morgan Kaufmann, San Francisco, CA, 2000.
Dan Pelleg and Andrew Moore.
[doi]  [BibTeX] 
A comparison of document clustering techniques.
In: KDD Workshop on Text Mining. 2000.
M. Steinbach, G. Karypis and V. Kumar.
[doi]  [BibTeX] 
A Comparison of Document Clustering Techniques.
In: KDD Workshop on Text Mining. 2000.
M. Steinbach, G. Karypis and V. Kumar.
[BibTeX] 
Accelerating Exact k -means Algorithms with Geometric Reasoning.
In: Knowledge Discovery and Data Mining, pages 277-281. 1999.
Dan Pelleg and Andrew Moore.
[doi]  [BibTeX] 
Refining initial points for K-Means clustering.
In: Proc. 15th International Conf. on Machine Learning, pages 91-99. Morgan Kaufmann, San Francisco, CA, 1998.
Paul S. Bradley and Usama M. Fayyad.
[doi]  [BibTeX] 

Miscellaneous

Clustering Algorithms.
1975.
J. Hartigan.
[BibTeX] 

Conference articles

Some Methods for Classification and Analysis of MultiVariate Observations.
In: L. M. L. Cam and J. Neyman, editors, Proc. of the fifth Berkeley Symposium on Mathematical Statistics and Probability, volume 1, pages 281-297. University of California Press, 1967.
J. B. MacQueen.
[BibTeX] 

Technical reports

ISODATA: A novel method of data analysis and pattern classification.
Stanford Research Institute, 1965.
G. Ball and D. Hall.
[BibTeX] 

Journal articles

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