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Volumn 2454 LNCS, Issue , 2002, Pages 52-62

CoFD: An algorithm for non-distance based clustering in high dimensional spaces

Author keywords

[No Author keywords available]

Indexed keywords

DATA WAREHOUSES; MAXIMUM LIKELIHOOD; WAREHOUSES; ALGORITHMS; DATA HANDLING;

EID: 84864857888     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-46145-0_6     Document Type: Conference Paper
Times cited : (6)

References (22)
  • 1
    • 0039253822 scopus 로고    scopus 로고
    • Finiding generalized projected clusters in high dimensional spaces
    • C. Aggarwal and P. S. Yu. Finiding generalized projected clusters in high dimensional spaces. In SIGMOOD-00, 2000.
    • (2000) SIGMOOD-00
    • Aggarwal, C.1    Yu, P.S.2
  • 3
    • 0032090765 scopus 로고    scopus 로고
    • Automatic subspace clustering for high dimensional data for data mining applications
    • R. Agrawal, J. Gehrke, D. Gunopulos, and P. Raghavan. Automatic subspace clustering for high dimensional data for data mining applications. In SIGMOD-98, 1998.
    • (1998) SIGMOD-98
    • Agrawal, R.1    Gehrke, J.2    Gunopulos, D.3    Raghavan, P.4
  • 4
    • 0016556021 scopus 로고
    • A new approach to manipulator control: The cerebellar model articlatioon controller (CMAC)
    • sep
    • J. S. Albus. A new approach to manipulator control: The cerebellar model articlatioon controller (CMAC). Trans. of the ASME, J. Dynamic Systems, Meaasurement, and Control, 97(3):220-227, sep 1975.
    • (1975) Trans. of the ASME, J. Dynamic Systems, Meaasurement, and Control , vol.97 , Issue.3 , pp. 220-227
    • Albus, J.S.1
  • 7
    • 0031571391 scopus 로고    scopus 로고
    • Connectivity of the mutual k-nearest-neighbor graph for clustering and outlier detection
    • M.R. Brito, E. Chavez, A. Quiroz, and J. Yukich. Connectivity of the mutual K-Nearest-Neighbor graph for clustering and outlier detection. Statistics and Probability Letters, 35:33-42, 1997.
    • (1997) Statistics and Probability Letters , vol.35 , pp. 33-42
    • Brito, M.R.1    Chavez, E.2    Quiroz, A.3    Yukich, J.4
  • 8
    • 84943175777 scopus 로고
    • AutoClass: A bayesian classification system
    • P. Cheeseman, J. Kelly, and M. Self. AutoClass: A bayesian classification system. In ICML'88, 1988.
    • (1988) ICML'88
    • Cheeseman, P.1    Kelly, J.2    Self, M.3
  • 9
    • 0038323536 scopus 로고    scopus 로고
    • Entropy-based subspace clustering for mining numericaldata
    • C-H Cheng, A. W-C Fu, and Y. Zhang. Entropy-based subspace clustering for mining numericaldata. In KDD-99, 1999.
    • (1999) KDD-99
    • Cheng, C.-H.1    Fu, A.W.-C.2    Zhang, Y.3
  • 10
    • 0024480421 scopus 로고
    • Entropy-constrained vector quantization
    • ASSP-37
    • P. A. Chou, T. Lookabaugh, and R. M. Gray. Entropy-constrained vector quantization. IEEE Trans., ASSP-37(1):31, 1989.
    • (1989) IEEE Trans. , Issue.1 , pp. 31
    • Chou, P.A.1    Lookabaugh, T.2    Gray, R.M.3
  • 11
    • 0004140078 scopus 로고    scopus 로고
    • An analysis of recent work on clustering algorithms
    • Dept. of Comp. Sci. & Eng.
    • D. Fasulo. An analysis of recent work on clustering algorithms. Technical Report 01-03-02, U. of Washington, Dept. of Comp. Sci. & Eng., 1999.
    • (1999) Technical Report 01-03-02, U. of Washington
    • Fasulo, D.1
  • 12
    • 0012904409 scopus 로고
    • Iterative optimization and simplification of hierarchical clusterings
    • Vanderbilt U., Dept. of Comp. Sci.
    • Douglas H. Fisher. Iterative optimization and simplification of hierarchical clusterings. TechnicalRep ort CS-95-01, Vanderbilt U., Dept. of Comp. Sci., 1995.
    • (1995) TechnicalRep Ort CS-95-01
    • Fisher, D.H.1
  • 17
    • 85021112585 scopus 로고
    • Feature subset selection using the wrapper method: Overfitting and dynamic search space technology
    • R. Kohavi and D. Sommerfield. Feature subset selection using the wrapper method: overfitting and dynamic search space technology. In KDD-95, 1995.
    • (1995) KDD-95
    • Kohavi, R.1    Sommerfield, D.2
  • 18
    • 0030157416 scopus 로고    scopus 로고
    • Mining quantitative association rules in large relational tables
    • R. Srikant and R. Agrawal. Mining quantitative association rules in large relational tables. In SIGMOD-96, 1996.
    • (1996) SIGMOD-96
    • Srikant, R.1    Agrawal, R.2
  • 19
    • 0001191328 scopus 로고    scopus 로고
    • A scalable approach to balanced, high-dimensional clustering of market-baskets
    • A. Strehl and J. Ghosh. A scalable approach to balanced, high-dimensional clustering of market-baskets. In HiPC-2000, 2000.
    • (2000) HiPC-2000
    • Strehl, A.1    Ghosh, J.2
  • 20
    • 0030157145 scopus 로고    scopus 로고
    • BIRCH: An efficient data clustering method for very large databases
    • T. Zhang, R. Ramakrishnan, and M. Livny. BIRCH: An efficient data clustering method for very large databases. In ACM SIGMOD Conference, 1996.
    • (1996) ACM SIGMOD Conference
    • Zhang, T.1    Ramakrishnan, R.2    Livny, M.3
  • 21
    • 84864852553 scopus 로고    scopus 로고
    • An algorithm for non-distance based clustering in high dimensional spaces
    • Computer Science Department, Rochester, NY
    • Shenghuo Zhu and Tao Li. An algorithm for non-distance based clustering in high dimensional spaces. TechnicalRep ort 763, University of Rochester, Computer Science Department, Rochester, NY, 2002.
    • (2002) TechnicalRep Ort 763, University of Rochester
    • Zhu, S.1    Li, T.2
  • 22
    • 0036086763 scopus 로고    scopus 로고
    • A non-distance based clustering algorithm
    • To appear
    • Shenghuo Zhu and Tao Li. A non-distance based clustering algorithm. In Proc. of IJCNN 2002, 2002. To appear
    • (2002) Proc. of IJCNN 2002
    • Zhu, S.1    Li, T.2


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