A genetic rule-based data clustering toolkit

Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002

Volumn 2, Issue , 2002, Pages 1238-1243

  Sarafis, I ^a   Zalzala, A M S ^a   Trinder, P W ^a  

^a HERIOT WATT UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

GENETIC ALGORITHMS;

CLUSTERING RULES; COMBINATORIAL PROBLEM; DATA CLUSTERING; DATABASE CLUSTERING; FITNESS FUNCTIONS; NON-BINARY; SIMILARITY BETWEEN OBJECTS; UNSUPERVISED CLASSIFICATION;

CLUSTERING ALGORITHMS;

EID: 84901398044     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2002.1004420     Document Type: Conference Paper

References (17)

1. J. Han and M. Kamber, "Data Mining: Concepts and Techniques," Morgan Kaufman Publishers, 2000.
2. U. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, R. Uthurusamy, "Advances in Knowledge Discovery and Data Mining", AAAI Press/The MIT Press, 1996.
3. R. O. Duda and P. E Hart, "Pattern Classification and Scene Analysis", John Wiley & Sons, NY, USA, 1973.
4. A. K. Jain and R. C. Dubes, "Algorithms for Clustering Data", Prentice-Hall, Englewood Cliffs, NJ, 1988.
5. L. Kaufiman, "Finding groups in data: an introduction to cluster Analysis", Wiley, New York, 1990.
6. E. Bonsma, M. Shackleton and R. Shipman, "Eos - an evolutionary and ecosystem research platform", BT Technology Journal, 18(14):24-3 1,2000.
7. Estivill-Castro, "Hybrid genetic algorithms are better for spatial clustering", Technical Report 99-08, Department of Computer Science and Software Engineering, The University of Newcastle, Callaghan, 2308 NSW, Australia, 1998.
8. David E. Goldberg, "Genetic Algorithms in Search, Optimization, and Machine Learning", Addison-Wesley, Reading, Massachusetts, 1989.
9. David W. Scott, "Multivariate Density Estimation: Theory", Practice and Visualization (John Wiley, New York, NY) 1992.
10. Zbigniew Michalewicz, "Genetic Algorithms + Data Structures = Evolution Program", Third Edition, Springer-Verlag, 1996.
11. S. Guha, R. Rastogi, and K. Shim, "CURE: An efficient clustering algorithm for large databases", In Proceedings of ACM SIGMOD International Conference on Management of Data, pages 73-84, New York, 1998.
12. G. Karypis, E.-H. Han, and V. Kumar, "Chameleon: Hierarchical clustering using dynamic modeling", IEEE Computer 32, pp. 68-75, August 1999.
13. T. Zhang, R. Ramakrishnan, and M. Livny, "BIRCH: An Efficient Data Clustering Method for Very Large Databases", In Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data, pp. 103-114, Montreal, Canada, 1996.
14. A. Hinneburg, D. A Keim, "An Efficient Approach to Clustering in Large Multimedia Databases with Noise", In Proceedings of the 4rd International Conference on Knowledge Discovery and Data Mining, AAAI Press, 1998.
15. W. Wang, J. Yang, and R. R. Muntz, "STING: A Statistical Information Grid Approach to Spatial Data Mining", In Proceedings of the 23rd VLDB, pp. 186-195, Athens, Greece, 1997.
16. K. Krishna and M. Murty, "Genetic K-means algorithm", IEEE Transactions on Systems, Man, and Cybernetics-PartB: Cybernetics, 29(3):433439, 1999.
17. L. O. Hall, I. B. Ozyurt, and J. C. Bezdek, "Clustering with a genetically optimized approach", IEEE Transactions on evolutionary Computation, 3(2): 103-112, July 1999