메뉴 건너뛰기




Volumn 19, Issue 8, 2007, Pages 1026-1041

An entropy weighting k-means algorithm for subspace clustering of high-dimensional sparse data

Author keywords

High dimensional data; K means clustering; Subspace clustering; Text clustering; Variable weighting

Indexed keywords

COMPUTATIONAL METHODS; DATA REDUCTION; PROBLEM SOLVING; TEXT PROCESSING;

EID: 34347228671     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2007.1048     Document Type: Article
Times cited : (602)

References (39)
  • 4
    • 30344483178 scopus 로고    scopus 로고
    • Document Clustering Using Locality Preserving Indexing
    • Dec
    • D. Cai, X. He, and J. Han, "Document Clustering Using Locality Preserving Indexing," IEEE Trans. Knowledge and Data Eng., vol. 17, no. 12, Dec. 2005.
    • (2005) IEEE Trans. Knowledge and Data Eng , vol.17 , Issue.12
    • Cai, D.1    He, X.2    Han, J.3
  • 5
    • 0025265976 scopus 로고
    • Medical Literature as a Potential Source of New Knowledge
    • Jan
    • D.R. Swanson, "Medical Literature as a Potential Source of New Knowledge," Bull. Medical Library Assoc., vol. 78, no. 1, Jan. 1990.
    • (1990) Bull. Medical Library Assoc , vol.78 , Issue.1
    • Swanson, D.R.1
  • 9
    • 0005287692 scopus 로고    scopus 로고
    • Local Dimensionality Reduction: A New Approach to Indexing High Dimensional Spaces
    • K. Chakrabarti and S. Mehrotra, "Local Dimensionality Reduction: A New Approach to Indexing High Dimensional Spaces," Proc. 26th Int'l Conf. Very Large Data Bases, pp. 89-100, 2000.
    • (2000) Proc. 26th Int'l Conf. Very Large Data Bases , pp. 89-100
    • Chakrabarti, K.1    Mehrotra, S.2
  • 11
    • 13844297591 scopus 로고    scopus 로고
    • A Practical Projected Clustering Algorithm
    • Nov
    • K.Y. Yip, D.W. Cheung, and M.K. Ng, "A Practical Projected Clustering Algorithm," IEEE Trans. Knowledge and Data Eng., vol. 16, no. 11, pp. 1387-1397, Nov. 2004.
    • (2004) IEEE Trans. Knowledge and Data Eng , vol.16 , Issue.11 , pp. 1387-1397
    • Yip, K.Y.1    Cheung, D.W.2    Ng, M.K.3
  • 12
    • 28444491389 scopus 로고    scopus 로고
    • On Discovery of Extremely Low-Dimensional Clusters Using Semi-Supervised Projected Clustering
    • K.Y. Yip, D.W. Cheung, and M.K. Ng, "On Discovery of Extremely Low-Dimensional Clusters Using Semi-Supervised Projected Clustering," Proc. 21st Int'l Conf. Data Eng., pp. 329-340, 2005.
    • (2005) Proc. 21st Int'l Conf. Data Eng , pp. 329-340
    • Yip, K.Y.1    Cheung, D.W.2    Ng, M.K.3
  • 13
    • 0002414638 scopus 로고
    • Synthesized Clustering: A Method for Amalgamating Clustering Bases with Differential Weighting Variables
    • W.S. Desarbo, J.D. Carroll, L.A. Clark, and P.E. Green, "Synthesized Clustering: A Method for Amalgamating Clustering Bases with Differential Weighting Variables," Psychometrika, vol. 49, pp. 57-78, 1984.
    • (1984) Psychometrika , vol.49 , pp. 57-78
    • Desarbo, W.S.1    Carroll, J.D.2    Clark, L.A.3    Green, P.E.4
  • 14
    • 0002048998 scopus 로고
    • A Validation Study of a Variable Weighting Algorithm for Cluster Analysis
    • G.W. Milligan, "A Validation Study of a Variable Weighting Algorithm for Cluster Analysis," J. Classification, vol. 6, pp. 53-71, 1989.
    • (1989) J. Classification , vol.6 , pp. 53-71
    • Milligan, G.W.1
  • 15
    • 0042312608 scopus 로고    scopus 로고
    • Feature Weighting in k-Means Clustering
    • D.S. Modha and W.S. Spangler, "Feature Weighting in k-Means Clustering," Machine Learning, vol. 52, pp. 217-237, 2003.
    • (2003) Machine Learning , vol.52 , pp. 217-237
    • Modha, D.S.1    Spangler, W.S.2
  • 16
    • 1842762839 scopus 로고    scopus 로고
    • An Optimization Algorithm for Clustering Using Weighted Dissimilarity Measures
    • Y. Chan, W. Ching, M.K. Ng, and J.Z. Huang, "An Optimization Algorithm for Clustering Using Weighted Dissimilarity Measures," Pattern Recognition, vol. 37, no. 5, pp. 943-952, 2004.
    • (2004) Pattern Recognition , vol.37 , Issue.5 , pp. 943-952
    • Chan, Y.1    Ching, W.2    Ng, M.K.3    Huang, J.Z.4
  • 17
    • 0346847567 scopus 로고    scopus 로고
    • Unsupervised Learning of Prototypes and Attribute Weights
    • H. Frigui and O. Nasraoui, "Unsupervised Learning of Prototypes and Attribute Weights," Pattern Recognition, vol. 37, no. 3, pp. 567-581, 2004.
    • (2004) Pattern Recognition , vol.37 , Issue.3 , pp. 567-581
    • Frigui, H.1    Nasraoui, O.2
  • 18
    • 13444303569 scopus 로고    scopus 로고
    • Simultaneous Clustering and Dynamic Keyword Weighting for Text Documents
    • Michael Berry, ed, pp, Springer
    • H. Frigui and O. Nasraoui, "Simultaneous Clustering and Dynamic Keyword Weighting for Text Documents," Survey of Text Mining, Michael Berry, ed., pp. 45-70, Springer, 2004.
    • (2004) Survey of Text Mining , pp. 45-70
    • Frigui, H.1    Nasraoui, O.2
  • 20
    • 8644255832 scopus 로고    scopus 로고
    • Clustering Objects on Subsets of Attributes
    • J.H. Friedman and J.J. Meulman, "Clustering Objects on Subsets of Attributes," J. Royal Statistical Soc. B, vol. 66, no. 4, pp. 815-849, 2004.
    • (2004) J. Royal Statistical Soc. B , vol.66 , Issue.4 , pp. 815-849
    • Friedman, J.H.1    Meulman, J.J.2
  • 23
    • 17044376078 scopus 로고    scopus 로고
    • Subspace Clustering for High Dimensional Data: A Review
    • L. Parsons, E. Haque, and H. Liu, "Subspace Clustering for High Dimensional Data: A Review," SIGKDD Explorations, vol. 6, no. 1, pp. 90-105, 2004.
    • (2004) SIGKDD Explorations , vol.6 , Issue.1 , pp. 90-105
    • Parsons, L.1    Haque, E.2    Liu, H.3
  • 25
    • 0242387333 scopus 로고    scopus 로고
    • Mafia: Efficient and Scalable Subspace Clustering for Very Large Data Sets
    • Technical Report CPDC-TR-9906-010, Northwest Univ
    • S. Goil, H. Nagesh, and A. Choudhary, "Mafia: Efficient and Scalable Subspace Clustering for Very Large Data Sets," Technical Report CPDC-TR-9906-010, Northwest Univ., 1999.
    • (1999)
    • Goil, S.1    Nagesh, H.2    Choudhary, A.3
  • 26
    • 0003136237 scopus 로고
    • Efficient and Effective Clustering Methods for Spatial Data Mining
    • Sept
    • R.T. Ng and J. Han, "Efficient and Effective Clustering Methods for Spatial Data Mining," Proc. 20th Int'l Conf. Very Large Data Bases, pp. 144-155, Sept. 1994.
    • (1994) Proc. 20th Int'l Conf. Very Large Data Bases , pp. 144-155
    • Ng, R.T.1    Han, J.2
  • 27
    • 20444480041 scopus 로고    scopus 로고
    • Findit: A Fast and Intelligent Subspace Clustering Algorithm Using Dimension Voting,
    • PhD dissertation, Korea Advanced Inst. of Science and Technology
    • K.G. Woo and J.H. Lee, "Findit: A Fast and Intelligent Subspace Clustering Algorithm Using Dimension Voting," PhD dissertation, Korea Advanced Inst. of Science and Technology, 2002.
    • (2002)
    • Woo, K.G.1    Lee, J.H.2
  • 28
    • 0036211103 scopus 로고    scopus 로고
    • δ-Clusters: Capturing Subspace Correlation in a Large Data Set
    • J. Yang, W. Wang, H. Wang, and P. Yu, "δ-Clusters: Capturing Subspace Correlation in a Large Data Set," Proc. 18th Int'l Conf. Data Eng., pp. 517-528, 2002.
    • (2002) Proc. 18th Int'l Conf. Data Eng , pp. 517-528
    • Yang, J.1    Wang, W.2    Wang, H.3    Yu, P.4
  • 30
    • 33947177850 scopus 로고
    • Optimal Variable Weighting for Ultrametric and Additive Tree Clustering
    • G. De Soete, "Optimal Variable Weighting for Ultrametric and Additive Tree Clustering," Quality and Quantity, vol. 20, pp. 169-180, 1986.
    • (1986) Quality and Quantity , vol.20 , pp. 169-180
    • De Soete, G.1
  • 31
    • 0000962917 scopus 로고
    • OVWTRE: A Program for Optimal Variable Weighting for Ultrametric and Additive Tree Fitting
    • G. De Soete, "OVWTRE: A Program for Optimal Variable Weighting for Ultrametric and Additive Tree Fitting," J. Classification, vol. 5, pp. 101-104, 1988.
    • (1988) J. Classification , vol.5 , pp. 101-104
    • De Soete, G.1
  • 32
    • 0035619721 scopus 로고    scopus 로고
    • Optimal Variable Weighting for Ultrametric and Additive Trees and k-Means Partitioning: Methods and Software
    • V. Makarenkov and P. Legendre, "Optimal Variable Weighting for Ultrametric and Additive Trees and k-Means Partitioning: Methods and Software," J. Classification, vol. 18, pp. 245-271, 2001.
    • (2001) J. Classification , vol.18 , pp. 245-271
    • Makarenkov, V.1    Legendre, P.2
  • 33
    • 14344255220 scopus 로고    scopus 로고
    • Locally Adaptive Techniques for Pattern Classification,
    • PhD dissertation
    • C. Domeniconi, "Locally Adaptive Techniques for Pattern Classification," PhD dissertation, 2002.
    • (2002)
    • Domeniconi, C.1
  • 35


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.