An approach for improving K-means algorithm on market segmentation

2010 International Conference on System Science and Engineering, ICSSE 2010

Volumn , Issue , 2010, Pages 368-372

  Wang, Haibo ^a   Huo, Da ^a   Huang, Jun ^a   Yan, Lixia ^b   Sun, Wei ^b   Li, Xianglu ^b   Xu, Yaquan ^c  

^a Texas A and M International University   (United States)

^b ZHONGYUAN UNIVERSITY OF TECHNOLOGY   (China)

^c VIRGINIA STATE UNIVERSITY   (United States)

Author keywords

Clustering; K means; Market segmentation; Silhouette coefficient

Indexed keywords

CLUSTER-BASED; CLUSTERING; CLUSTERING METHODS; COMMERCIAL SOFTWARE; K-MEANS; K-MEANS ALGORITHM; MARKET SEGMENTATION; MARKETING APPLICATION; SILHOUETTE COEFFICIENT;

COMMERCE; SYSTEMS SCIENCE;

CLUSTERING ALGORITHMS;

EID: 77957578410     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSSE.2010.5551709     Document Type: Conference Paper

References (22)

1. C. M. Schaffer and P. E. Green, "Cluster-based market segmentation: Some further comparisons of alternative approaches," Journal of the Market Research Society, vol. 40, pp. 155-163, 1998.
2. E. J. Deeds, N. V. Dokholyan, E. I. Shakhnovich, "Protein Evolution within a Structural Space," Biophys. J., vol. 85, pp. 2962-2972, November 1, 2003.
3. S. J. Arnold, "A Test for Clusters," Journal of Marketing Research, vol. 16, pp. 545-551, 1979.
4. A. M. Krieger and P. E. Green, "ModifYing cluster-based segments to enhance agreement with an exogenous response variable," Journal of Marketing Research, vol. 33, pp. 351-363, 1996.
5. C. Anil, J. D. Carroll, and P. E. Green, "A feature-based approach to market segmentation via overlapping K-centroids clustering," Journal of Marketing Research, vol. 34, pp. 370-377, 1997.
6. H. Hruschka, W. Fettes and M. Probst, "Market segmentation by maximum likelihood clustering using choice elasticities," European Journal of Operational Research, vol. 154, pp. 779-786, 2004.
7. P. V. Balakrishnan, M. C. Cooper, V.S. Jacob, and P.A. Lewis, "Comparative performance of the FSCL neural net and K-means algorithm for market segmentation," European Journal of Operational Research, vol. 93, pp. 346-357, 1996.
8. C. W. Chen and J. Luo, "Image Segmentation via Adaptive K-Mean Clustering and Knowledge-Based Morphological Operations," IEEE Transactions on Image Processing, vol. 7, p. 1673, 1998.
9. H. Hruschka and M. Natter, "Comparing performance of feedforward neural nets and K-means for cluster-based market segmentation," European Journal of Operational Research, vol. 114, pp. 346-353, 1999.
10. T. Kanungo, D. M. Mount, N. S. Netanyahu, C. Piatko, R. Silverman and A. Y. Wu, "An Efficient k-Means Clustering Algorithm: Analysis and Implementation," IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 24, p. 881, 2002.
11. R. Mileris and R. Glinskienė, "RINKOS SEGMENT A VIMAS KLASTERINES ANALIZĖS K-VIDURKIIJ METODU. (Lithuanian)," MARKET SEGMENTATION BASED ON CLUSTER ANALYSIS METHOD OF K-MEANS. (English), pp. 432-438, 2007.
12. P. S. La Rosa, A. Nehorai, H. Eswaran, C. Lowery, and H. Preissl "Detection of Uterine MMG Contractions Using a Multiple Change Point Estimator and the K-Means Cluster Algorithm," IEEE Transactions on Biomedical Engineering, vol. 55, pp. 453-467, 2008.
13. M. Mignotte, "Segmentation by Fusion of Histogram-Based K-Means Clusters in Different Color Spaces," IEEE Transactions on Image Processing, vol. 17, pp. 780-787, 2008.
14. N. A. M. Isa, S.A. Salamah, U.K. Ngah., "Adaptive Fuzzy Moving Kmeans Clustering Algorithm for Image Segmentation," IEEE Transactions on Consumer Electronics, vol. 55, pp. 2145-2153, 2009.
15. M. R. Anderberg, Cluster Analysis for Applications. New York: Academic Press, Inc., 1973.
16. J. A. Hartigan, Clustering Algorithms. New York: John Wiley & Sons, Inc, 1975.
17. J. McQueen, "Some methods for classi cation and analysis of multivariate observations," in Proceeding of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, 1967, pp. 281- 297.
18. R. J. Kuo, L.M. Ho and C.M. Hu, "Integration of self-organizing feature map and K-means algorithm for market segmentation," Computers & Operations Research, vol. 29, p. 1475, 2002.
19. R. J. Kuo, Y.L. An, H.S. Wang and W.J. Chung., "Integration of self-organizing feature maps neural network and genetic K-means algorithm for market segmentation," Expert Systems with Applications, vol. 30, pp. 313-324, 2006.
20. S. A. Mingoti and J. O. Lima, "Comparing SOM neural network with Fuzzy c-means, K-means and traditional hierarchical clustering algorithms," European Journal of Operational Research, vol. 174, pp. 1742-1759, 2006.
21. L. Kaufinan and P. J. Rousseeuw, Groups in Data: An Introduction to Cluster Analysis: Wiley, 1990.
22. J. Lattin, J. D. Carroll and P. E. Green., Analyzing Multivariate Data: Duxbury 2003.