An efficient k-means clustering algorithm: analysis and implementation

10.1023/A:1009783824328

bradley, 1998, Scaling Clustering Algorithms to Large Databases, Proc Fourth Int'l Conf Knowledge Discovery and Data Mining, 9

10.1016/0196-6774(91)90007-L

du, 1999, Centroidal Voronoi Tesselations: Applications and Algorithms, SIAM Rev, 41, 637, 10.1137/S0036144599352836

dasgupta, 2000, A Two-Round Variant of EM for Gaussian Mixtures, Proc 16th Conf Uncertainty in Artificial Intelligence (UAI-2000), 152

10.1109/SFFCS.1999.814639

10.1016/0167-8655(85)90053-4

fayyad, 1996, Advances in Knowledge Discovery and Data Mining

faber, 1994, Clustering and the Continuous Algorithm, Los Alamos Science, 22, 138

ester, 1995, A Database Interface for Clustering in Large Spatial Databases, Proc First Int'l Conf Knowledge Discovery and Data Mining (KDD-95), 94

duda, 1973, Pattern Classification and Scene Analysis

feller, 1968, An Introduction to Probability Theory and Its Applications

forgey, 1965, Cluster Analysis of Multivariate Data: Efficiency vs. Interpretability of Classification, Biometrics, 21, 768

fukunaga, 1990, Introduction to statistical pattern recognition

10.1007/978-1-4615-3626-0

garey, 1979, Computers and Intractability A Guide to the Theory of NP-Completeness

10.1145/237218.237406

inaba, 1997

jain, 1988, Algorithms for clustering data

10.1145/177424.178042

10.1109/34.824819

kanungo, 2000, The Analysis of a Simple Clustering Algorithm

10.1145/336154.336189

10.1145/331499.331504

kanungo, 1999, Computing Nearest Neighbors for Moving Points and Applications to Clustering, Proc 10th Ann ACM-SIAM Symp Discrete Algorithms, 931

maneewongvatana, 1999, Analysis of Approximate Nearest Neighbor Searching with Clustered Point Sets, Proc Workshop Algorithm Eng and Experiments (ALENEX '99)

macqueen, 1967, Some Methods for Classification and Analysis of Multivariate Observations, Proc Fifth Berkeley Symp Math Statistics and Probability, 1, 281

10.1109/TIT.1982.1056489

kolliopoulos, 1999, A Nearly Linear-Time Approximation Scheme for the Euclidean Problem, Proc Seventh Ann European Symp Algorithms, 362

kohonen, 1989, Self-Organization and Associative Memory, 10.1007/978-3-642-88163-3

kaufman, 1990, Finding Groups in Data An Introduction to Cluster Analysis

matousek, 2000, On Approximate Geometric, Discrete and Computational Geometry, 24, 61, 10.1007/s004540010019

moore, 1998, Very Fast EM-Based Mixture Model Clustering Using Multiresolution kd-Trees, Proc Conf Neural Information Processing Systems

mount, 1997, ANN: A Library for Approximate Nearest Neighbor Searching, Proc Center for Geometric Computing Second Ann Fall Workshop Computational Geometry

ng, 1994, Efficient and Effective Clustering Methods for Spatial Data Mining, Proc 20th Int'l Conf Very Large Databases, 144

mangasarian, 1997, Mathematical Programming in Data Mining, Data Mining and Knowledge Discovery, 1, 183, 10.1023/A:1009735908398

ball, 1964, Some Fundamental Concepts and Synthesis Procedures for Pattern Recognition Preprocessors, Proc Int'l Conf Microwaves Circuit Theory and Information Theory

10.1109/TPAMI.1984.4767478

10.1145/293347.293348

10.1016/S0925-7721(00)00022-5

10.1145/276698.276718

alsabti, 1998, An Efficient Clustering Algorithm, Proc First Workshop High Performance Data Mining

pelleg, 2000, : Extending with Efficient Estimation of the Number of Clusters, Proc 17th Int'l Conf Machine Learning

10.1007/s00453-001-0110-y

pelleg, 1999, Accelerating Exact Algorithms with Geometric Reasoning, Proc ACM SIGKDD Int'l Conf Knowledge Discovery and Data Mining, 277

preparata, 1990, Computational Geometry An Introduction

10.1214/aop/1176993713

bradley, 1998, Refining Initial Points for K-means Clustering, Proc 15th Int'l Conf Machine Learning, 91

bottou, 1995, Convergence Properties of the Algorithms, Advances in Neural Information Processing Systems 7, 585

10.1145/361002.361007