Ant clustering algorithm with K-harmonic means clustering

Expert Systems with Applications

Volumn 37, Issue 12, 2010, Pages 8679-8684

  Jiang, Hua ^a   Yi, Shenghe ^a   Li, Jing ^a   Yang, Fengqin ^a   Hu, Xin ^a  

^a NORTHEAST NORMAL UNIVERSITY   (China)

Author keywords

Ant clustering algorithm; Clustering; K harmonic means clustering; K means

Indexed keywords

HARMONIC ANALYSIS;

ANT CLUSTERING ALGORITHM; CLUSTERING; DATA DISTRIBUTION; K-HARMONIC MEANS CLUSTERING; K-MEANS; K-MEANS ALGORITHM; LOCAL OPTIMAL SOLUTION; NEW CLUSTERING ALGORITHMS;

CLUSTERING ALGORITHMS;

EID: 77957852859     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.06.061     Document Type: Article

References (20)

1. Chu, S.,&Roddick, J. (2003). A clustering algorithm using Tabu search approach with simulated annealing for vector quantization. Chinese Journal of Electronics, 12(3), 349-353.
2. Dalli, A. (2003). Adaptation of the F-measure to cluster-based Lexicon quality evaluation. In EACL 2003. Budapest.
3. Deneubourg, J.-L., Goss,S., Franks, N., Sendova-Franks, A., Detrain, C.,&Chretien, L. (1991). The dynamics of collective sorting: Robot-like ants and ant-like robots. In Proceedings of the first international conference on simulation of adaptive behavior (pp. 356-365).
4. Güngör, Z.,&Ünler, A. (2007). K-harmonic means data clustering with simulated annealing heuristic. Applied Mathematics and Computation, 184, 199-209.
5. Güngör, Z.,&Ünler, A. (2008). K-harmonic means data clustering with tabu-search method. Applied Mathematical Modelling, 32, 1115-1125.
6. Hammerly, G.,&Elkan, C. (2002). Alternatives to the k-means algorithm that find better clusterings. In: Proceedings of the 11th international conference on information and knowledge management (pp. 600-607).
7. Handl, J., Knowles, J.,&Dorigo, M. (2003). On the performance of ant-based clustering. Design and application of hybrid intelligent systems. Frontiers in Artificial Intelligence and Applications, 104, 204-213.
8. Handl, J.,&Meyer, B. (2007). Ant-based and swarm-based clustering. Swarm Intelligence, 1, 95-113.
9. Huang, C. H., Pan, J. S., Lu, Z. H., Sun, S. H.,&Hang, H. M. (2001). Vector quantization based on genetic simulated annealing. Signal Processing, 81, 1513-1523.
10. Jain, A. K., Murty, M. N.,&Flynn, P. J. (1999). Data clustering: A review. ACM Computational Survey, 31(3), 264-323.
11. Kanade, P.M.,&Hall, L.O. (2003). Fuzzy ants as a clustering concept. In 22nd International conference of the north american fuzzy information processing society (NAFIPS) (pp. 227-232).
12. Kao, Y. T., Zahara, E.,&Kao, I. W. (2008). A hybridized approach to data clustering. Expert Systems with Applications, 34, 1754-1762.
13. Khan, S. S.,&Ahmad, A. (2004). Cluster center initialization algorithm for K-means clustering. Pattern Recognition Letters, 25, 1293-1302.
14. Liu, B. (2006). Web Data Mining. Chicago: Springer. Chapter 4.
15. Lumer, E.D,&Faieta, B. (1994). Diversity and adaptation in populations of clustering ants. In Proceedings of the third international conference on the simulation of adaptive behavior (Vol. 3) (pp. 499-508).
16. Vizine, A. L.,&de Castro, L. N. (2005). Towards improving clustering ants: An adaptive ant clustering algorithm. Informatica, 29, 143-154.
17. Xu, R. (2005). Survey of clustering algorithms. IEEE Transactions on Neural Networks, 16, 645-678.
18. Yang, F. Q.,&Sun, T. L. (2009). Particle swarm optimization based K-harmonic means data clustering. Expert Systems with Applications, 36, 9847-9852.
19. Zhang, B., Hsu, M.,&Dayal, U. (1999). K-harmonic means - A data clustering algorithm. Technical Report HPL-1999-2124 Hewlett-Packard Laboratories.
20. Zhang, B., Hsu, M.,&Dayal, U. (2000). K-harmonic means. In International workshop on temporal, spatial and spatio-temporal data mining, TSDM2000. Lyon, France, September 12.