On the impact of dissimilarity measure in κ-modes clustering algorithm

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 29, Issue 3, 2007, Pages 503-507

  Ng, Michael K ^a   Li, Mark Junjie ^a   Huang, Joshua Zhexue ^b   He, Zengyou ^c  

^a HONG KONG BAPTIST UNIVERSITY   (Hong Kong)

^b UNIVERSITY OF HONG KONG   (Hong Kong)

^c HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

modes algorithm; Categorical data; Clustering; Data mining

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; DATA MINING; HEURISTIC ALGORITHMS; OPTIMIZATION;

CATEGORICAL DATA; DISSIMILARITY MEASURE;

CLUSTERING ALGORITHMS;

ALGORITHM; ARTICLE; ARTIFACT; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CLUSTER ANALYSIS; COMPARATIVE STUDY; EVALUATION; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFACTS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; INFORMATION STORAGE AND RETRIEVAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 33847349252     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2007.53     Document Type: Article

References (13)

1. B. Andreopoulos, A. An, and X. Wang, "Clustering the Internet Topology at Multiple Layers," WSEAS Trans. Information Science and Applications, vol. 2, no. 10, pp. 1625-1634, 2005.
2. A. Chaturvedi, P. Green, and J. Carroll, "K-Modes Clustering," J. Classification, vol. 18, pp. 35-55, 2001.
3. K.C. Gowda and E. Diday, "Symbolic Clustering Using a New Dissimilarity Measure," Pattern Recognition, vol. 24, no. 6, pp. 567-578, 1991.
4. Z. He, S. Deng, and X. Xu, "Improving k-Modes Algorithm Considering Frequencies of Attribute Values in Mode," Proc. Int'l Conf. Computational Intelligence and Security, pp. 157-162, 2005.
5. Z. Huang, "A Fast Clustering Algorithm to Cluster Very Large Categorical Data Sets in Data Mining," Proc. SIGMOD Workshop Research Issues on Data Mining and Knowledge Discovery, pp. 1-8, 1997.
6. Z. Huang, "Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values," Data Mining and Knowledge Discovery, vol. 2, no. 3, pp. 283-304, 1998.
7. Z. Huang and M. Ng, "A Fuzzy k-Mode Algorithm for Clustering Categorical Data," IEEE Trans. Fuzzy Systems, vol. 7, no. 4, 1999.
8. Z. Huang and M. Ng, "A Note on k-Modes Clustering," J. Classification, vol. 20, pp. 257-261, 2003.
9. A.K. Jain and R.C. Dubes, Algorithms for Clustering Data. Prentice Hall, 1988.
10. L. Kaufman and P.J. Rousseeuw, Finding Groups in Data - An Introduction to Cluster Analysis. Wiley, 1990.
11. V. Manganaro, S. Paratore, E. Alessi, S. Coffa, and S. Cavallaro, "Adding Semantics to Gene Expression Profiles: New Tools for Drug Discovery," Current Medicinal Chemistry, vol. 12, pp. 1149-1160, 2005.
12. O. San, V. Huynh, and Y. Nakamori, "An Alternative Extension of the k-Means Algorithm for Clustering Categorical Data," Int'l J. Applied Math. and Computer Science, vol. 14, no. 2, pp. 241-247, 2004.
13. UCI Machine Learning Repository, http://www.ics.uci.edu/mlearn/ MLRepository.html, 2006.