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Volumn , Issue , 2005, Pages 25-32

U*F clustering: A new performant "cluster- mining" method based on segmentation of self-organizing maps

Author keywords

Clustering; Data mining; Self Organizing Maps; SOM segmentation; U matrix

Indexed keywords

ARTIFICIAL DATASETS; CLUSTERING; CLUSTERING APPROACH; CLUSTERING METHODS; CLUSTERING RESULTS; COMPUTATION COSTS; NUMBER OF CLUSTERS; U-MATRIX;

EID: 84890308263     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (21)

References (12)
  • 1
    • 84942935904 scopus 로고    scopus 로고
    • Efficient hierarchical clustering algorithms using partially overlapping partitions
    • M. Dash and H. Liu (2001), Efficient hierarchical clustering algorithms using partially overlapping partitions, Lecture Notes in Computer Science, Vol. 2035, p. 495-507.
    • (2001) Lecture Notes in Computer Science , vol.2035 , pp. 495-507
    • Dash, M.1    Liu, H.2
  • 2
    • 0020068152 scopus 로고
    • Self-organized formation of topologically correct feature maps
    • T. Kohonen (1982), Self-Organized formation of topologically correct feature maps, Biological Cybernetics, Vol. 43, p. 59-69.
    • (1982) Biological Cybernetics , vol.43 , pp. 59-69
    • Kohonen, T.1
  • 3
    • 56149114998 scopus 로고    scopus 로고
    • Fast semi-automatic segmentation algorithm for self-organizing maps
    • Bruges, 28-30 avril 2004
    • D. Opolon & F. Moutarde (2004), Fast semi-automatic segmentation algorithm for Self-Organizing Maps, In Proc. of ESANN'2004, Bruges, 28-30 avril 2004, p. 507-512.
    • (2004) Proc. of ESANN'2004 , pp. 507-512
    • Opolon, D.1    Moutarde, F.2
  • 4
    • 0002535204 scopus 로고
    • Self-organizing neural networks for visualization and classification
    • Dortmund (Germany), April 1992
    • A. Ultsch (1992), Self-Organizing Neural Networks for Visualization and Classification, In Proc. Conf. Soc. for Information and Classification, Dortmund (Germany), April 1992.
    • (1992) Proc. Conf. Soc. for Information and Classification
    • Ultsch, A.1
  • 5
    • 24944572401 scopus 로고    scopus 로고
    • Maps for the visualization of high-dimensional data spaces
    • Kyushu (Japan)
    • A. Ultsch (2003), Maps for the Visualization of high-dimensional Data Spaces, In Proc. WSOM'03, Kyushu (Japan), p. 225-230.
    • (2003) Proc. WSOM'03 , pp. 225-230
    • Ultsch, A.1
  • 6
    • 26944499910 scopus 로고    scopus 로고
    • *-matrix: A tool to visualize clusters in high dimensional data
    • University of Marburg (Germany)
    • *-Matrix: a Tool to visualize Clusters in high dimensional Data, In Research report Dept. of Mathematics and Computer Science, University of Marburg (Germany), No. 36.
    • (2003) Research Report Dept. of Mathematics and Computer Science , Issue.36
    • Ultsch, A.1
  • 8
    • 0006585767 scopus 로고
    • Self-organizing-feature-maps versus statistical clustering methods: A benchmark
    • University of Marburg, Research Report 0994
    • A. Ultsch & C. Vetter (1994), Self-Organizing-Feature-Maps versus statistical clustering methods: a benchmark. FG Neuroinformatik & Kuenstliche Intelligenz, University of Marburg, Research Report 0994.
    • (1994) FG Neuroinformatik & Kuenstliche Intelligenz
    • Ultsch, A.1    Vetter, C.2
  • 9
    • 0010985453 scopus 로고    scopus 로고
    • Self-organizing map in matlab: The SOM toolbox
    • Espoo, Finland, November 1999
    • J. Vesanto et al. (1999), Self-organizing map in Matlab: the SOM toolbox, In Proceedings of the Matlab DSP Conference, Espoo, Finland, November 1999, p. 35-40.
    • (1999) Proceedings of the Matlab DSP Conference , pp. 35-40
    • Vesanto, J.1
  • 10
    • 38049168357 scopus 로고    scopus 로고
    • SOM-based data visualization methods
    • J. Vesanto (1999), SOM-based data visualization methods, Intelligent Data Analysis, Vol. 3 (2).
    • (1999) Intelligent Data Analysis , vol.3 , Issue.2
    • Vesanto, J.1
  • 11
    • 0003642575 scopus 로고    scopus 로고
    • Using SOM in data mining
    • Helsinki University of Technology
    • J. Vesanto (2000), Using SOM in data mining, Licentiate thesis, Helsinki University of Technology.
    • (2000) Licentiate Thesis
    • Vesanto, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.