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Volumn 36, Issue 3 PART 2, 2009, Pages 6050-6061

External validation measures for K-means clustering: A data distribution perspective

Author keywords

Cluster validation; External criteria; K means; Normalization

Indexed keywords

CLUSTER ANALYSIS; CLUSTERING ALGORITHMS;

EID: 58349088069     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2008.06.093     Document Type: Article
Times cited : (59)

References (31)
  • 1
    • 33750506476 scopus 로고    scopus 로고
    • Model-based evaluation of clustering validation measures
    • Brun M., Sima C., Hua J., Lowey J., Carroll B., Suh E., et al. Model-based evaluation of clustering validation measures. Pattern Recognition 40 2007 (2007) 807-824
    • (2007) Pattern Recognition , vol.40 , Issue.2007 , pp. 807-824
    • Brun, M.1    Sima, C.2    Hua, J.3    Lowey, J.4    Carroll, B.5    Suh, E.6
  • 4
    • 77952375075 scopus 로고    scopus 로고
    • Dhillon, I., Mallela, S., & Modha, D. (2003). Information-theoretic co-clustering. In Proceedings of the 9th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 89-98).
    • Dhillon, I., Mallela, S., & Modha, D. (2003). Information-theoretic co-clustering. In Proceedings of the 9th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 89-98).
  • 8
    • 0348096294 scopus 로고    scopus 로고
    • Clustering validity checking methods: Part ii
    • Halkidi M., Batistakis Y., and Vazirgiannis M. Clustering validity checking methods: Part ii. SIGMOD Record 31 3 (2002) 19-27
    • (2002) SIGMOD Record , vol.31 , Issue.3 , pp. 19-27
    • Halkidi, M.1    Batistakis, Y.2    Vazirgiannis, M.3
  • 12
    • 58349110467 scopus 로고    scopus 로고
    • Karypis, G. (2007). Cluto-Software for clustering high-dimensional datasets, version 2.1.1. .
    • Karypis, G. (2007). Cluto-Software for clustering high-dimensional datasets, version 2.1.1. .
  • 14
    • 58349087586 scopus 로고    scopus 로고
    • Lewis, D. (1991). Evaluating text categorization. In Proceedings of speech and natural language workshop (pp. 312-318).
    • Lewis, D. (1991). Evaluating text categorization. In Proceedings of speech and natural language workshop (pp. 312-318).
  • 15
    • 0001457509 scopus 로고
    • Some methods for classification and analysis of multivariate observations
    • Proceedings of the 5th Berkeley symposium on mathematical statistics and probability. Cam L.M.L., and Neyman J. (Eds), University of California Press
    • MacQueen J. Some methods for classification and analysis of multivariate observations. In: Cam L.M.L., and Neyman J. (Eds). Proceedings of the 5th Berkeley symposium on mathematical statistics and probability. Statistics Vol. 1 (1967), University of California Press
    • (1967) Statistics , vol.1
    • MacQueen, J.1
  • 16
    • 58349085908 scopus 로고    scopus 로고
    • MathWorks (2007). K-means clustering in statistics toolbox. .
    • MathWorks (2007). K-means clustering in statistics toolbox. .
  • 17
    • 9444274777 scopus 로고    scopus 로고
    • Meila, M. (2003). Comparing clusterings by the variation of information. In Proceedings of the 16th annual conference on computational learning theory (pp. 173-187).
    • Meila, M. (2003). Comparing clusterings by the variation of information. In Proceedings of the 16th annual conference on computational learning theory (pp. 173-187).
  • 18
    • 31844440880 scopus 로고    scopus 로고
    • Meila, M. (2005). Comparing clusterings-An axiomatic view. In Proceedings of the 22th international conference on machine learning (pp. 577-584).
    • Meila, M. (2005). Comparing clusterings-An axiomatic view. In Proceedings of the 22th international conference on machine learning (pp. 577-584).
  • 20
    • 0036993190 scopus 로고    scopus 로고
    • Slonim, N., Friedman, N., & Tishby, N. (2002). Unsupervised document classification using sequential information maximization. In Proceedings of the 25th annual international ACM SIGIR conference.
    • Slonim, N., Friedman, N., & Tishby, N. (2002). Unsupervised document classification using sequential information maximization. In Proceedings of the 25th annual international ACM SIGIR conference.
  • 21
    • 58349120762 scopus 로고    scopus 로고
    • Steinbach, M., Karypis, G., & Kumar, V. (2000). A comparison of document clustering techniques. In Workshop on text mining, the 6th ACM SIGKDD international conference on knowledge discovery and data mining.
    • Steinbach, M., Karypis, G., & Kumar, V. (2000). A comparison of document clustering techniques. In Workshop on text mining, the 6th ACM SIGKDD international conference on knowledge discovery and data mining.
  • 22
    • 58349115785 scopus 로고    scopus 로고
    • Strehl, A., Ghosh, J., & Mooney, R. (2000). Impact of similarity measures on web-page clustering. In AAAI workshop on AI for web search (pp. 58-64).
    • Strehl, A., Ghosh, J., & Mooney, R. (2000). Impact of similarity measures on web-page clustering. In AAAI workshop on AI for web search (pp. 58-64).
  • 24
    • 58349115152 scopus 로고    scopus 로고
    • TREC (2007). Text retrieval conference. .
    • TREC (2007). Text retrieval conference. .
  • 25
    • 58349095313 scopus 로고    scopus 로고
    • van Dongen, S. (2000). Performance criteria for graph clustering and markov cluster experiments. Tech. Rep. INS=R0012, Centrum voor Wiskunde en Informatica.
    • van Dongen, S. (2000). Performance criteria for graph clustering and markov cluster experiments. Tech. Rep. INS=R0012, Centrum voor Wiskunde en Informatica.
  • 26
    • 49749114842 scopus 로고    scopus 로고
    • Wu, J., Xiong, H., Chen, J., & Zhou, W. (2007). A generalization of proximity functions for K-means. In Proceedings of the 2007 IEEE international conference on data mining.
    • Wu, J., Xiong, H., Chen, J., & Zhou, W. (2007). A generalization of proximity functions for K-means. In Proceedings of the 2007 IEEE international conference on data mining.
  • 27
    • 33749563831 scopus 로고    scopus 로고
    • Xiong, H., Wu, J., & Chen, J. (2007). K-means clustering versus validation measures: A data distribution perspective. In Proceedings of the 12th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 779-784).
    • Xiong, H., Wu, J., & Chen, J. (2007). K-means clustering versus validation measures: A data distribution perspective. In Proceedings of the 12th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 779-784).
  • 28
    • 3543085722 scopus 로고    scopus 로고
    • Criterion functions for document clustering: Experiments and analysis
    • Zhao Y., and Karypis G. Criterion functions for document clustering: Experiments and analysis. Machine Learning 55 3 (2004) 311-331
    • (2004) Machine Learning , vol.55 , Issue.3 , pp. 311-331
    • Zhao, Y.1    Karypis, G.2
  • 29
    • 24044537630 scopus 로고    scopus 로고
    • Hierarchical clustering algorithms for document datasets
    • Zhao Y., and Karypis G. Hierarchical clustering algorithms for document datasets. Data Mining and Knowledge Discovery 10 2 (2005) 141-168
    • (2005) Data Mining and Knowledge Discovery , vol.10 , Issue.2 , pp. 141-168
    • Zhao, Y.1    Karypis, G.2
  • 30
    • 2142687208 scopus 로고    scopus 로고
    • A unified framework for model-based clustering
    • Zhong S., and Ghosh J. A unified framework for model-based clustering. Journal of Machine Learning Research 4 6 (2004) 1001-1037
    • (2004) Journal of Machine Learning Research , vol.4 , Issue.6 , pp. 1001-1037
    • Zhong, S.1    Ghosh, J.2
  • 31
    • 24944501423 scopus 로고    scopus 로고
    • Generative model-based document clustering: A comparative study
    • Zhong S., and Ghosh J. Generative model-based document clustering: A comparative study. Knowledge and Information Systems 8 3 (2005) 374-384
    • (2005) Knowledge and Information Systems , vol.8 , Issue.3 , pp. 374-384
    • Zhong, S.1    Ghosh, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.