[1] Gordon A D. Hierarchical clustering[M]. Arabie P, Hubert L J, De Soete G, Eds. Singapore: World Scientific Publishers, 1996. [2] Lozano J A, Larranagea P. Applying genetic algorithms to search for the best hierarchical clustering of a dataset[J]. Pattern Recognition Letters, 1999, 20(9): 911-918. [3] Dorigo M. Optimization, learning and natural algorithms[D]. Italy: Politecnico di Milano, 1992. [4] Jain A K, Murty M N, Flynn P J. Data clustering: a review[J]. ACM Computing Surveys, 1999, 31(3): 264-323. [5] Xu Rui, Wunsch D. Survey of clustering algorithms[J]. IEEE Transactions on Neural Networks, 2005, 16(3): 645-678. [6] Karypis G, Han E, Kumar V. Chameleon: hierarchical clustering using dynamic modeling[J]. IEEE Computer, 1999, 32(8): 68-75. [7] Geva A. Hierarchical unsupervised fuzzy clustering[J]. IEEE Trans, Fuzzy Syst, 1999, 7(6): 723-733. [8] Morzy T, Wojciechowski M, Zakrzewicz M. Pattern-oriented hierarchical clustering, advances in databases and information systems[C]// Proceeding of the 3rd East Eur Conf. Slovenia: LNCS 1691, 1999: 179-190. [9] Azzag H, Venturini G, Oliver A, et al. A hierarchical ant based clustering algorithm and its use in three real-world applications[J]. Eur J Oper Res, 2007, 179(3): 906-922. [10] Monmarche N, Slimane M, Venturini G. AntClass: discovery of clusters in numeric data by an hybridization of an ant colony with the kmeans algorithm[C]// Extraction des Connaissances et Apprentissage: Apprentissage et Tvolution. 1999: 131-166. [11] Chaimontree S, Atkinson K, Coenen F. Best clustering configuration metrics: towards multiagent based clustering[C]// Proc of the 6th Int Conf Advanced Data Mining and Applications (ADMA’10). Chongqing: Springer, LNAI, 6440, 2010: 48-59. [12] Frank A, Asuncion A. UCI machine learning repository[EB/OL]. Irvine, CA: University of California, School of Information and Computer Science, 2010. http: //archive. ics. uci. edu/ml. [13] Frank E, Hall M, Holmes G, et al. Weka-a machine learning workbench for data mining[M]. Springer, Maimon O, Rokach L(Eds). Berlin: Data Mining and Knowledge Discovery Handbook, 2005: 1305-1314. |