Arthur,David
Vassilvitskii,Sergei
k-means++: the advantages of careful seeding
Society for Industrial and Applied Mathematics
1027–1035
2007
Bickel,S.
Scheffer,T.
Multi–View Clustering
2004
Savaresi,SergioM.
Boley,Daniel
A comparative analysis on the bisecting K-means and the PDDP clustering algorithms.
Intell. Data Anal.
8
345-362
2004
Hotho,A
Staab,S.
Stumme,G.
Wordnet improves text document clustering
2003
Zhao,Ying
Karypis,George
Evaluation of hierarchical clustering algorithms for document datasets
ACM Press
515–524
2002
Hotho,Andreas
Maedche,Alexander
Staab,Steffen
Text Clustering Based on Good Aggregations
IEEE Computer Society
607–608
2001
Wagstaff,Kiri
Cardie,Claire
Rogers,Seth
Schrödl,Stefan
Constrained K-means Clustering with Background Knowledge.
577-584
2001
Kirsten,Mathias
Wrobel,Stefan
Extending K-Means Clustering to First-Order Representations
Springer
1866
112-129
2000
Pelleg,Dan
Moore,Andrew
$X$-means: Extending $K$-means with Efficient Estimation of the Number of Clusters
Morgan Kaufmann, San Francisco, CA
727–734
2000
Steinbach,M.
Karypis,G.
Kumar,V.
A comparison of document clustering techniques
2000
Steinbach,M.
Karypis,G.
Kumar,V.
A Comparison of Document Clustering Techniques
2000
Pelleg,Dan
Moore,Andrew
Accelerating Exact k -means Algorithms with Geometric Reasoning
277-281
1999
Bradley,PaulS.
Fayyad,UsamaM.
Refining initial points for K-Means clustering
Morgan Kaufmann, San Francisco, CA
91–99
1998
Hartigan,J.
Clustering Algorithms
John Wiley and Sons, New York
1975
MacQueen,J.B.
Some Methods for Classification and Analysis of MultiVariate Observations
University of California Press
1
281-297
1967
Ball,G.
Hall,D.
ISODATA: A novel method of data analysis and pattern classification
1965
Forgy,E.
Cluster Analysis of Multivariate Data: Efficiency versus Interpretability of Classification
Biometrics
21
768-769
1965