메뉴 건너뛰기




Volumn , Issue , 2004, Pages 218-225

Document clustering via adaptive subspace iteration

Author keywords

Adaptive subspace identification; Alternating optimization; Document clustering; Factor analysis

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); DATA PROCESSING; EIGENVALUES AND EIGENFUNCTIONS; IDENTIFICATION (CONTROL SYSTEMS); LEARNING SYSTEMS; MAXIMUM LIKELIHOOD ESTIMATION; PATTERN RECOGNITION;

EID: 8644250640     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1008992.1009031     Document Type: Conference Paper
Times cited : (95)

References (48)
  • 2
    • 0032090765 scopus 로고    scopus 로고
    • Automatic subspace clustering of high dimensional data for data mining applications
    • Agrawal, R., Gehrke, J., Gunopulos, D., & Raghavan, P. (1998). Automatic subspace clustering of high dimensional data for data mining applications. ACM SIGMOD Conference (pp. 94-105).
    • (1998) ACM SIGMOD Conference , pp. 94-105
    • Agrawal, R.1    Gehrke, J.2    Gunopulos, D.3    Raghavan, P.4
  • 6
    • 0002969516 scopus 로고
    • Probabilistic aspects in cluster analysis
    • O. Opitz (Ed.). Berlin: Springer-verlag
    • Bock, H.-H. (1989). Probabilistic aspects in cluster analysis. In O. Opitz (Ed.), Conceptual and numerical analysis of data, 12-44. Berlin: Springer-verlag.
    • (1989) Conceptual and Numerical Analysis of Data , pp. 12-44
    • Bock, H.-H.1
  • 11
    • 0034370539 scopus 로고    scopus 로고
    • Identification of almost invariant aggregates in reversible nearly coupled markov chain
    • Deuflhard, P., Huisinga, W. Fischer, A. & Schutte, C. (2000). Identification of almost invariant aggregates in reversible nearly coupled markov chain. Linear Algebra and Its Applications, 315, 39-59.
    • (2000) Linear Algebra and Its Applications , vol.315 , pp. 39-59
    • Deuflhard, P.1    Huisinga, W.2    Fischer, A.3    Schutte, C.4
  • 16
    • 80455131402 scopus 로고    scopus 로고
    • Sufficient dimensionality reduction
    • Globerson, A., & Tishby, N. (2003). Sufficient dimensionality reduction. J. Mach. Learn. Res., 3, 1307-1331.
    • (2003) J. Mach. Learn. Res. , vol.3 , pp. 1307-1331
    • Globerson, A.1    Tishby, N.2
  • 18
    • 21344435020 scopus 로고
    • Simultaneous clustering of rows and columns
    • Govaert, G. (1985). Simultaneous clustering of rows and columns. Control and Cybernetics, 437-458.
    • (1985) Control and Cybernetics , pp. 437-458
    • Govaert, G.1
  • 19
    • 0032091595 scopus 로고    scopus 로고
    • CURE: An efficient clustering algorithm for large databases
    • Guha, S., Rastogi, R., & Shim, K. (1998). CURE: an efficient clustering algorithm for large databases. ACM SIGMOD Conference (pp. 73-84).
    • (1998) ACM SIGMOD Conference , pp. 73-84
    • Guha, S.1    Rastogi, R.2    Shim, K.3
  • 20
    • 0026925324 scopus 로고
    • New spectral methods for ratio cut partitioning and clustering
    • Hagen, L., & Kahng, A. B. (1992). New spectral methods for ratio cut partitioning and clustering. IEEE Trans. Computer-Aided Design, 11, 1074-1085.
    • (1992) IEEE Trans. Computer-aided Design , vol.11 , pp. 1074-1085
    • Hagen, L.1    Kahng, A.B.2
  • 28
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • Lee, D. D., & Seung, H. S. (1999). Learning the parts of objects by non-negative matrix factorization. Nature, 401, 788-791.
    • (1999) Nature , vol.401 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 39
    • 0002096830 scopus 로고    scopus 로고
    • Document clustering using word clusters via the information bottleneck method
    • Slonim, N., & Tishby, N. (2000). Document clustering using word clusters via the information bottleneck method. ACM SIGIR 2000 (pp. 208-215).
    • (2000) ACM SIGIR 2000 , pp. 208-215
    • Slonim, N.1    Tishby, N.2
  • 43
    • 1542347778 scopus 로고    scopus 로고
    • Document clustering based on non-negative matrix factorization
    • Xu, W., Liu, X., & Gong, Y. (2003). Document clustering based on non-negative matrix factorization. ACM SIGIR 2003 (pp. 267-273).
    • (2003) ACM SIGIR 2003 , pp. 267-273
    • Xu, W.1    Liu, X.2    Gong, Y.3
  • 44
    • 0030157145 scopus 로고    scopus 로고
    • BIRCH: An efficient data clustering method for very large databases
    • Zhang, T., Ramakrishnan, R., & Livny, M. (1996). BIRCH: an efficient data clustering method for very large databases. ACM SIGMOD Conference (pp. 103-114).
    • (1996) ACM SIGMOD Conference , pp. 103-114
    • Zhang, T.1    Ramakrishnan, R.2    Livny, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.