Document clustering into an unknown number of clusters using a genetic algorithm

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2807, Issue , 2003, Pages 43-49

  Casillas, A ^a   De Gonzalez Lena M T ^b   Martinez R ^b  

^a UNIVERSITY OF THE BASQUE COUNTRY UPV EHU   (Spain)

^b UNIVERSIDAD REY JUAN CARLOS   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; COSTS; EVOLUTIONARY ALGORITHMS; MATRIX ALGEBRA; OPTIMIZATION; QUERY LANGUAGES; SEARCH ENGINES; ALGORITHMS; APPROXIMATION ALGORITHMS; CLUSTER ANALYSIS; GENETIC ALGORITHMS; INFORMATION RETRIEVAL;

CENTROIDS; CLUSTERS; COMPUTATIONAL COSTS; OPTIMAL SOLUTIONS; DOCUMENT CLUSTERING; FITNESS FUNCTIONS; K CLUSTER; K-VALUES; NUMBER OF CLUSTERS; STOPPING RULE;

GENETIC ALGORITHMS; CLUSTERING ALGORITHMS;

EID: 9444279511     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-39398-6_7     Document Type: Conference Paper

References (13)

1. Calinski, T., Harabasz, J.: "A Dendrite Method for Cluster Analysis". Communications in Statistics, 3(1), (1974) 1-27.
2. Chu, S.C., Roddick, J.F., Pan, J.S.: "An Incremental Multi-Centroid, Multi-Run Sampling Scheme for k-medoids-based Algortihms-Extended Report". Proceedings of the Third International Conference on Data Mining Methods and Databases, Data Mining III, (2002), 553-562.
3. Estivill-Castro, V., Murray, A.T.: "Spatial Clustering for Data Mining with Genetic Algorithms". Proceedings of the International ICSC Symposium on Engineering of Intelligent Systems, EIS-98, (1998).
4. Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning, Addison Wesley Longman, Inc. (2002).
5. Gordon, A. D.: Classification, Chapman & Hall/CRC, (1999).
6. Holland, J. H.: Adaptation in natural and artificial system, Ann Arbor: The University of Michigan Press. (1975).
7. Lucasius, C.B., Dane, A.D., Kateman, G.: "On k-medoid clustering of large data sets with the aid of Genetic Algorithm: background, feasibility and comparison". Analytica Chimica Acta, Elsevier Science Publishers B.V. 283(3), (1993) 647-669.
8. Makagonov, P., Alexandrov, M., Gelbukh, A.: "Selection of typical documents in a document flow". Advances in Communications and Software Technologies, WSEAS Press (2002) 197-202.
9. Merz, P., Zell, A.: "Clustering Gene Expresion Profiles with Memetic Algorithms". Lecture Notes in Computer Science 2439, Springer-Verlag Berlin (2002) 811-820.
10. Michalewicz, Z.: Genetic algorithms + data structures = evolution programs, Springer Comp. (1996).
11. Milligan, G. W., Cooper, M.C.: "An Examination of Procedures for Determining the Number of Clusters in a Data Set". Psychometrik, 58(2), (1985) 159-179.
12. Murthy, C.A., Chowdhury, N.: "In search of Optimal Clusters Using Genetic Algorithms". Pattern Recognition Letters, 17(8), (1996), 825-832.
13. Sarkar, M., Yegnanarayana, B., Khemani, D.: "A clustering algorithm using an evolutionary programming-based approach". Pattern Recognition Letters, 18, (1997) 975-986.