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Michael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, and Jörg Sander.
OPTICS: ordering points to identify the clustering structure.
In Proceedings of the ACM SIGMOD International Conference on Management of Data, Philadephia, Pennsylvania, USA, pages 49-60, 1999.

C. J. Alpert and A. B. Kahng.
Recent directions in netlist partitioning: A survey.
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J. A. Barnett.
Computational methods for a mathematical theory of evidence.
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Amir Ben-Dor, Ron Shamir, and Zohar Yakhini.
Clustering gene expression patterns.
Journal of Computational Biology, 6(3/4):281-297, 1999.

Anselm Blumer, Andrzej Ehrenfeucht, David Haussler, and Manfred K. Warmuth.
Occam's razor.
Information processing Letters, 24:377-380, 1987.

P. S. Bradley, U. M. Fayyad, and C. Reina.
Scaling clustering algorithms to large databases.
In Knowledge Discovery and Data Mining, pages 9-15, 1998.

Kurt D. Bollacker and Joydeep Ghosh.
A supra-classifier architecture for scalable knowledge reuse.
In Proc. Int'l Conf. on Machine Learning (ICML-98), pages 64-72, July 1998.

Kurt D. Bollacker and Joydeep Ghosh.
Effective supra-classifiers for knowledge base construction.
Pattern Recognition Letters, 20(11-13):1347-52, November 1999.

A. Banerjee and J. Ghosh.
Clickstream clustering using weighted longest common subsequences.
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A. Banerjee and J. Ghosh.
On scaling up balanced clustering algorithms.
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D. Boley, M. Gini, R. Gross, E. Han, K. Hastings, G. Karypis, V. Kumar, B. Mobasher, and J. Moore.
Partitioning-based clustering for web document categorization.
Decision Support Systems, 27:329-341, 1999.

Michael W. Berry, Bruce Hendrickson, and Padma Raghavan.
Sparse matrix reordering schemes for browsing hypertext.
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C. Bishop.
Neural Networks for Pattern Recognition.
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M. J. A. Berry and G. Linoff.
Data Mining Techniques for Marketing, Sales and Customer Support.
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J. P. Barthelemy, B. Laclerc, and B. Monjardet.
On the use of ordered sets in problems of comparison and consensus of classifications.
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A. Blum and T. Mitchell.
Combining labeled and unlabeled data with co-training.
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L. Breiman.
Bagging predictors.
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Ricardo Baeza-Yates.
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Rich Caruana.
Learning many related tasks at the same time with backpropagation.
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M. Craven, D. DiPasquo, D. Freitag, A. McCallum, T. Mitchell, K. Nigam, and S. Slattery.
Learning to extract symbolic knowledge from the world wide web.
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G. A. Carpenter and S. Grossberg.
The ART of adaptive pattern recognition by a self-organizing neural network.
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S. V. Chakaravathy and J. Ghosh.
Scale based clustering using a radial basis function network.
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K. Chang and J. Ghosh.
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Chaomei Chen.
Visualising semantic spaces and author co-citation networks in digital libraries.
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Douglass R. Cutting, David Karger, Jan O. Pedersen, and John W. Tukey.
Scatter/gather: A cluster-based approach to browsing large document collections.
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P. Chan and S. Stolfo.
A comparative evaluation of voting and meta-learning on partitioned data.
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Peter Cheeseman and John Stutz.
Bayesian classification (AutoClass): Theory and results.
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Thomas M. Cover and Joy A. Thomas.
Elements of Information Theory.
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B. Dasarathy.
Decision Fusion.
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H. Drucker, C. Cortes, L. D. Jackel, Y. LeCun, and V. Vapnik.
Boosting and other ensemble methods.
Neural Computation, 6(6):1289-1301, 1994.

Scott C. Deerwester, Susan T. Dumais, Thomas K. Landauer, George W. Furnas, and Richard A. Harshman.
Indexing by latent semantic analysis.
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R. O. Duda and P. E. Hart.
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Wiley, New York, 1973.

R. O. Duda, P. E. Hart, and D. G. Stork.
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T. G. Dietterich.
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A. P. Dempster, N. M. Laird, and D. B. Rubin.
Maximum likelihood from incomplete data via the EM algorithm.
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Inderjit S. Dhillon and Dharmendra S. Modha.
Concept decompositions for large sparse text data using clustering.
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Inderjit S. Dhillon, Dharmendra S. Modha, and W. Scott Spangler.
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M. Ester, H. Kriegel, J. Sander, and X. Xu.
A density-based algorithm for discovering clusters in large spatial databases with noise.
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Michael B. Eisen, Paul T. Spellman, Patrick O. Brown, and David Botstein.
Cluster analysis and display of genome-wide expression patterns.
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Brian Everitt.
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W. B. Frakes and R. Baeza-Yates.
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M. Fiedler.
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M. Fiedler.
A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory.
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Douglas Fisher.
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Douglas Fisher.
Improving inference through conceptual clustering.
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C. Faloutsos and K. Lin.
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C. M. Fiduccia and R. M. Mattheyses.
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W. Frakes.
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U. M. Fayyad, C. Reina, and P. S. Bradley.
Initialization of iterative refinement clustering algorithms.
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J. H. Friedman.
An overview of predictive learning and function approximation.
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K. Fukanaga.
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J. Ghosh, S. Beck, and C. C. Chu.
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M. A. Gluck and J. E. Corter.
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A. Gelman, J. B. Carlin, H. S. Stern, and D. B. Rubin.
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G. K. Gupta and J. Ghosh.
Detecting seasonal trends and cluster motion visualization for very high dimensional transactional data.
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D. R. Gusfield and R. W. Irving.
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Michael R. Garey and David S. Johnson.
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J. R. Gilbert, G. L. Miller, and S. Teng.
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S. Guha, R. Rastogi, and K. Shim.
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S. Guha, R. Rastogi, and K. Shim.
Rock: a robust clustering algorithm for categorical attributes.
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Joydeep Ghosh and Alexander Strehl.
Clustering and visualization of retail market baskets.
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Gunjan K. Gupta, Alexander Strehl, and Joydeep Ghosh.
Distance based clustering of association rules.
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John A. Hartigan.
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S. Hashem.
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S. Haykin.
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P. Hansen and B. Jaumard.
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E. Han, G. Karypis, V. Kumar, and B. Mobasher.
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Timo Honkela, Samuel Kaski, Krista Lagus, and Teuvo Kohonen.
WEBSOM--self-organizing maps of document collections.
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J. Han, M. Kamber, and A. K. H. Tung.
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B. Hendrickson and R. Leland.
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B. Hendrickson and R. Leland.
An improved spectral graph partitioning algorithm for mapping parallel computations.
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P. J. Huber.
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Piotr Indyk.
A sublinear-time approximation scheme for clustering in metric spaces.
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A. K. Jain and R. C. Dubes.
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T. S. Jaakkola and D. Haussler.
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E. Johnson and H. Kargupta.
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A. K. Jain, M. N. Murty, and P. J. Flynn.
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T. Joachims.
Text categorization with support vector machines: Learning with many relevant features.
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George Karypis, Rajat Aggarwal, Vipin Kumar, and Shashi Shekhar.
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S. Kumar and J. Ghosh.
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George Karypis, Eui-Hong Han, and Vipin Kumar.
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H. Kargupta, W. Huang, K. Sivakumar, and E. Johnson.
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Daniel A. Keim and Hans-Peter Kriegel.
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G. Karypis and V. Kumar.
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G. Karypis and V. Kumar.
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B. Kernighan and S. Lin.
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Branko Kavsek, Nada Lavrac, and Anuska Ferligoj.
Consensus decision trees: Using consensus hierarchical clustering for data relabelling and reduction.
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Teuvo Kohonen.
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H. Kargupta, B. Park, D. Hershberger, and E. Johnson.
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L. Kaufmann and P. Rousseeuw.
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S. Kannan, T. Warnow, and S. Yooseph.
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Ken Lang.
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Mala Mehrotra.
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Raymond J. Mooney and Loriene Roy.
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Alexander Strehl and Joydeep Ghosh.
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Alexander Strehl and Joydeep Ghosh.
Value-based customer grouping from large retail data-sets.
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Alexander Strehl and Joydeep Ghosh.
Relationship-based visualization of high-dimensional data clusters.
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Alexander Strehl and Joydeep Ghosh.
Cluster ensembles - a knowledge reuse framework for combining partitionings.
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Alexander Strehl and Joydeep Ghosh.
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Alexander Strehl, Joydeep Ghosh, and Raymond J. Mooney.
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M. Steinbach, G. Karypis, and V. Kumar.
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Alexander Strehl 2002-05-03