This is a (surely incomplete) bibliography on Conceptual Clustering, Concept Formation and related topics from Statistics and Cognitive Psychology. Note that references for the former areas are incomplete, they are either general texts or commonly referred publications.

If you are interested in more general information about clustering you can take a look at David Dowe's clustering and mixture modelling page.

Any comments, corrections, or additions are welcome. Send to Luis Talavera

Last update: May 2000.


Bibliography of Conceptual Clustering

W. Ahn and D. L. Medin.
A two-stage model of category construction.
Cognitive Science, (16):81-121, 1992.

J. R. Anderson and M. Matessa.
An incremental bayesian algorithm for categorization.
In D. H. Fisher, M.J. Pazzani, and P. Langley, editors, Concept formation: Knowledge and experience in unsupervised learning, pages 45-70. Morgan Kauffmann, San Mateo, CA, 1991.

J. R. Anderson and M. Matessa.
Explorations of an incremental, bayesian algorithm for categorization.
Machine Learning, (9):275-308, 1992.

J. Béjar, U. Cortés, and M. Domingo.
Using domain theory to bias classification processes in ill-domains.
In Proceedings of the Forth Iberoamerican Conference on Artificial Intelligence,IBERAMIA-94, pages 187-197, 1996.

J. Béjar, U. Cortés, R. Sanguesa, and M. Poch.
Experiments with domain knowledge in knowledge discovery.
In Proceedings of the 1st. International Conference on the Practical Application of Knowledge Discovery and Data Mining, London,UK, 1997.

G. Bisson
Conceptual clustering in a first order logic representation
In Proceedings of the 10th European Conference on Artificial Intelligence, pages 458-462, 1992.

G. Biswas, J. Weinberg, Q. Yang and G. Koller.
Conceptual clustering and exploratory data analysis.
In Proceedings of the Eight International Workshop on Machine Learning, pages 591-595, Evanston, IL, 1991.

P. Cheeseman, J. Kelly, M. Self, J. Stutz, W. Taylor, and D. Freeman.
AutoClass: A bayesian classification system.
In Proceedings of the Fifth International Workshop on Machine Learning, pages 54-64. Morgan Kauffmann, San Mateo, CA, 1988.

M. Devaney and A. Ram.
Efficient feature selection in conceptual clustering.
In Machine Learning: Proceedings of the Fourteenth International Conference, Nashville, TN, 1997.

R. Duda and P. Hart.
Pattern classification and scene analysis.
John Wiley & Sons, 1973.

B. Everitt.
Cluster analysis.
Heinemann, London, 1981.

D. H. Fisher.
Knowledge acquisition via incremental conceptual clustering.
Machine Learning, (2):139-172, 1987.

D. H. Fisher.
Knowledge acquisition via incremental conceptual clustering.
PhD thesis, University of California, Irvine, 1987.

D. H. Fisher.
Optimization and simplification of hierarchical clusterings.
In Proceedings of the First International Conference on Knowledge Discovery and Data Mining, pages 118-123, Montreal, Quebec, Canada, 1995. AAAI Press.

D. H. Fisher.
Iterative optimization and simplification of hierarchical clusterings.
Journal of Artificial Intelligence Research, (4):147-179, 1996.

D. H. Fisher and P. Chan.
Statistical guidance in symbolic learning.
Annals of Mathematics and Artificial Intelligence, (2):135-148, 1990.

D. H. Fisher and P. Langley.
Conceptual clustering and its relation to numerical taxonomy.
In W. A. Gale, editor, Artificial Intelligence and Statistics. Addison-Wesley, Reading,MA, 1986.

D. H. Fisher and M. J. Pazzani.
Computational models of concept learning.
In D. H. Fisher, M.J. Pazzani, and P. Langley, editors, Concept formation: Knowledge and experience in unsupervised learning, pages 3-43. Morgan Kauffmann, San Mateo, CA, 1991.

D. H. Fisher and M. J. Pazzani.
Concept formation in context.
In D. Fisher, M. J. Pazzani, and P. Langley, editors, Concept Formation: Knowledge and Experience in unsupervised learning, pages 307-322. Morgan Kaufmann, San Mateo, CA, 1991.

D. H. Fisher and M. J. Pazzani.
Theory-guided concept formation.
In D. Fisher, M. J. Pazzani, and P. Langley, editors, Concept Formation: Knowledge and Experience in unsupervised learning, pages 165-177. Morgan Kaufmann, San Mateo, CA, 1991.

D. H. Fisher, L. Xu, and N. Zard.
Ordering effects in clustering.
In Proceedings of the Ninth International Conference on Machine Learning, pages 163-168, 1992.

J. H. Gennari.
Focused concept formation.
In Proceedings of the Fifth International Workshop on Machine Learning, pages 379-382. Morgan Kauffmann, 1989.

J. H. Gennari.
Concept formation and attention.
In Proceedings of the Seventh Annual Conference of the Cognitive Science Society, pages 724-728, Irvine,CA, 1991. Lawrence Erlbaum Associates.

J. H. Gennari, P. Langley, and D. Fisher.
Models of incremental concept formation.
Artificial Intelligence, (40):11-61, 1989.

M. A. Gluck and J. E. Corter.
Information, uncertainty and the utility of categories.
In Proceedings of the Seventh Annual Conference of the Cognitive Science Society, pages 283-287. Lawrence Erlbaum Associates, 1985.

A. D. Gordon.
A review of hierarchical classification.
J. R. Statist. Soc. A., (150):119-137, 1987.

M. Hadzikadic and D. Yun.
Concept formation by incremental conceptual clustering.
In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, pages 831-836. Morgan Kaufmann, 1989.

S. J. Hanson.
Conceptual clustering and categorization: Bridging the gap between induction and causal models.
In R. S. Michalski and Y. Kodratoff, editors, Machine Learning: An Artificial Ingelligence Appproach (Volume III), chapter 9, pages 235-268. Morgan Kauffmann, San Mateo, CA, 1990.

S. J. Hanson and M. Bauer.
Conceptual clustering, categorization and polymorphy.
Machine Learning, (3):343-372, 1989.

A. K. Jain and R. C. Dubes.
Algorithms for cluster analysis.
Prentice Hall, Englewood Cliffs, NJ, 1988.

G. V. Jones.
Identifying basic categories.
Psychological Bulletin, (94):423-428, 1985.

F. Kilander and C. G. Jansson.
Cobbit-a control procedure for Cobweb in the presence of concept drift.
In P. B. Bradzil, editor, Proceedings of the European Conference on Machine Learning, pages 244-261. Springer Verlag, 1993.

P. Langley.
Order effects in incremental learning.
In P. Reimann and H. Spada, editors, Learning in humans and machines: Towards an Interdisciplinary Learning Science. Pergamon, 1995.

M. Lebowitz.
Experiments with incremental concept formation: UNIMEM.
Machine Learning, (2):103-138, 1987.

M. Lebowitz.
Deferred commitment in UNIMEM: waiting to learn.
In Proceedings of the Fifth International Conference on Machine Learning, pages 80-86, 1988.

J. N. MacGregor.
The effects of order in learning. Classifications by example: heuristics for finding the optimal order.
Artificial Intelligence, (34):361-370, 1988.

J. D. Martin
Learning Overlapping Categories.
In Proceedings of the Twelfth Annual Conference of the Cognitive Science Society. Cambridge, MA: Lawrence Erlbaum Associates. 1990.

J. D. Martin
DP1: Supervised and unsupervised clustering.
European Conference on Machine Learning, Catania, Italy. 1994.

J. D. Martin
Goal directed clustering.
In the AAAI Spring Symposium on Goal-Directed Learning, Palo Alto, CA. 1994.

J. D. Martin
Clustering full-text documents.
Workshop on Data Engineering, International Joint Conference on Artificial Intelligence , Montreal, Canada. 1995.

J. D. Martin and D. O. Billman
Variability bias and category learning.
In Proceedings of the Eighth International Workshop on Machine Learning , pages 90-94. Evanston, IL: Morgan Kaufmann. 1991.

J. D. Martin and D. O. Billman
The acquisition and use of overlapping concepts.
Machine Learning, 16. 1994

D. L. Medin.
Concepts and conceptual structure.
American Psychologist, 44(12):1469-1481, 1989.

D. L. Medin and A. Ortony.
Psychological essentialism.
In S. Vosniadou and A. Ortony, editors, Similarity and analogical reasoning. Cambridge University Press, New York, 1989.

D. L. Medin and M. M. Schaffer.
Context theory of classification learning.
Psychological Review, 85:207-238, 1978.

D. L. Medin and E. E. Smith.
Concepts and concept formation.
Annual Review of Psychology, (35):113-138, 1984.

D. L. Medin and W. D. Wattenmaker.
Family resemblance, conceptual cohesiveness and category construction.
Cognitive Psychology, (19):242-279, 1987.

D. L. Medin, W. D. Wattenmaker, and R. S. Michalski.
Constraints and preferences in inductive learning: an experimental study of human and machine performance.
Cognitive Science, (11):299-339, 1987.

C. B. Mervis and E. Rosch.
Categorization of natural objects.
Annual Review of Psychology, (32):89-115, 1981.

R. S. Michalski and R. E. Stepp.
Learning from observation: Conceptual clustering.
In R. S. Michalski, J. G. Carbonell, and T. M. Mitchell, editors, Machine Learning: An Artificial intelligence approach, pages 331-363. Morgan Kauffmann, San Mateo, CA, 1983.

R. J. Mooney.
Explanation-Based learning as concept formation.
In D. H. Fisher, M.J. Pazzani, and P. Langley, editors, Concept formation: Knowledge and experience in unsupervised learning, pages 179-205. Morgan Kauffmann, San Mateo, CA, 1991.

G. L. Murphy.
Cue validity and levels of categorization.
Psychological Bulletin, 91:174-177, 1982.

G. L. Murphy and D. L. Medin.
The role of theories in conceptual coherence.
Psychological Review, 92:289-316, 1985.

R. M . Nosofsky.
Attention, similarity and the identification-categorization relationship.
Journal of Experimental Psychology Research: General, (115):39-57, 1986.

D. N. Osherson and E. E. Smith.
On the adecuacy of prototype theory as a theory of concepts.
Cognition, (9):35-58, 1981.

Y. Reich.
Macro and micro perspectives of multistrategy learning.
In R. S. Michalski and G. Tecuci, editors, Machine Learning: A Multistrategy Approach, volume IV, pages 379-401. Morgan Kauffmann, San Francisco, CA, 1994.

Y. Reich and S. Fenves.
The formation and use of abstract concepts in design.
In D. H. Fisher, M.J. Pazzani, and P. Langley, editors, Concept formation: Knowledge and experience in unsupervised learning, pages 323-353. Morgan Kauffmann, San Mateo, CA, 1991.

E. Rosch and C. B. Mervis.
Family resemblances: studies in the internal structure of categories.
Cognitive Psychology, 7:573-606, 1975.

E. Rosch, C. B. Mervis, W. D. Gray, D. M. Johnson, and P. Boyes-Braem.
Basic objects in natural categories.
Cognitive Psychology, 8:573-605, 1976.

J. Roure and L. Talavera.
Robust incremental clustering with bad orderings: a new strategy.
In Sixth Iberoamerican Conference on Artificial Intelligence, IBERAMIA-98, volume 1484 of Lecture Notes in Artificial Intelligence, Lisbon, Portugal, 1998. Springer Verlag.

E. E. Smith and D. L. Medin.
Categories and concepts.
Harvard University Press, Cambridge,MA, 1981.

P. H. A. Sneath and R. R. Sokal.
Numerical Taxonomy.
W. H. Freeman, San Francisco, 1973.

R. E. Stepp.
Concepts in conceptual clustering.
In Proceedings of the Tenth International Joint Conference on Artificial Intelligence, pages 211-213, Milan, Italy, 1987. Morgan Kauffmann.

R. E. Stepp and R. S. Michalski.
Conceptual clustering: Inventing goal oriented classifications of structured objects.
In R. S. Michalski, J. G. Carbonell, and T. M. Mitchell, editors, Machine Learning: An artificial intelligence approach, volume II. Morgan Kauffmann, San Mateo, CA, 1986.

L. Talavera.
From unsupervised learning to data mining: linking cognition and data analysis.
In Proceedings of Jornades d'Intel.ligència Artificial: Noves Tendències, Lleida, Spain, 1997.

L. Talavera.
Exploring efficient attribute prediction in hierarchical clustering.
In Proceedings of the Sixth Iberoamerican Conference on Artificial Intelligence, IBERAMIA-98, Lisbon, Portugal, Ed. Colibri. 1998.

L. Talavera and J. Roure.
A buffering strategy to avoid ordering effects in clustering.
In Proceedings of the Tenth European Conference on Machine Learning, volume 1398 of Lecture Notes in Artificial Intelligence, Chemnitz, Germany, 1998. Springer.

J. T. Tou and R. C. Gonzalez.
Pattern Recognition Principles.
Addison-Wesley, Reading,MA, 1974.

J.J. F. Vasco, C. Faucher, and E. Chouraqui.
A knowledge acquisition tool for multi-perspective concept formation.
In 9th European Knowledge Acquisition Workshop, EKAW'96, pages 227-244. Springer Verlag, 1996.

E. J. Wisniewski and D. L. Medin.
Harpoons and long sticks: the interaction of theory and similarity in rule induction.
In D. H. Fisher, M.J. Pazzani, and P. Langley, editors, Concept formation: Knowledge and experience in unsupervised learning, pages 237-278. Morgan Kauffmann, San Mateo, CA, 1991.


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