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Volumn 14, Issue 3, 2008, Pages 273-298

Robust projected clustering

Author keywords

Clustering numerical and categorical data; Projected clustering; Subspace clustering

Indexed keywords

PARAMETER ESTIMATION;

EID: 41149085604     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-007-0090-6     Document Type: Article
Times cited : (60)

References (26)
  • 5
    • 0033536012 scopus 로고    scopus 로고
    • Broad patterns of gene expression revealed by clustering of tumor and normal colon tissues probed by oligonucleotide arrays
    • Alon U, Barkai N, Notterman D, Gish K, Ybarra S, Mack D and Levine A (1999). Broad patterns of gene expression revealed by clustering of tumor and normal colon tissues probed by oligonucleotide arrays. Proc Natl Acad Sci USA 96(12):6745-6750
    • (1999) Proc Natl Acad Sci USA , vol.96 , Issue.12 , pp. 6745-6750
    • Alon, U.1    Barkai, N.2    Notterman, D.3    Gish, K.4    Ybarra, S.5    Mack, D.6    Levine, A.7
  • 8
    • 0002629270 scopus 로고
    • Maximum likelihood for incomplete data via the EM algorithm
    • Dempster A, Laird N and Rubin D (1977). Maximum likelihood for incomplete data via the EM algorithm. J Roy Stat Soc 39:1-38
    • (1977) J Roy Stat Soc , vol.39 , pp. 1-38
    • Dempster, A.1    Laird, N.2    Rubin, D.3
  • 9
    • 26844445118 scopus 로고    scopus 로고
    • Subspace clustering for high dimensional categorical data
    • Gan G and Wu J (2004). Subspace clustering for high dimensional categorical data. ACM SIGKDD Explor Newslett 6(2):87-94
    • (2004) ACM SIGKDD Explor Newslett , vol.6 , Issue.2 , pp. 87-94
    • Gan, G.1    Wu, J.2
  • 11
    • 85132256511 scopus 로고    scopus 로고
    • A general approach to clustering in large databases with noise
    • Hinneburg A and Keim D (2003). A general approach to clustering in large databases with noise. Knowl Inf Syst 5(4):387-415
    • (2003) Knowl Inf Syst , vol.5 , Issue.4 , pp. 387-415
    • Hinneburg, A.1    Keim, D.2
  • 12
    • 2942588997 scopus 로고    scopus 로고
    • Density-connected subspace clustering for high-dimensional data
    • In: Berry M, Dayal U, Kamath C, Skilicorn D (eds) Lake Buena Vista, April 2004
    • Kailing K, Kriegel H, Kröger P (2004) Density-connected subspace clustering for high-dimensional data. In: Berry M, Dayal U, Kamath C, Skilicorn D (eds) Proceedings of the SIAM international conference on data mining, Lake Buena Vista, April 2004, pp 1-11
    • (2004) Proceedings of the SIAM International Conference on Data Mining , pp. 1-11
    • Kailing, K.1    Kriegel, H.2    Kröger, P.3
  • 16
    • 14644424597 scopus 로고    scopus 로고
    • Projective clustering by histograms
    • Ng K, Fu A and Wong C (2005). Projective clustering by histograms. IEEE Trans Knowl Data Eng 17(3):369-383
    • (2005) IEEE Trans Knowl Data Eng , vol.17 , Issue.3 , pp. 369-383
    • Ng, K.1    Fu, A.2    Wong, C.3
  • 17
    • 17044376078 scopus 로고    scopus 로고
    • Subspace clustering for high dimensional data: A review
    • Parsons L, Haque E and Liu H (2004). Subspace clustering for high dimensional data: A review. ACM SIGKDD Explor Newslett 6(1):90-105
    • (2004) ACM SIGKDD Explor Newslett , vol.6 , Issue.1 , pp. 90-105
    • Parsons, L.1    Haque, E.2    Liu, H.3
  • 19
    • 84950439147 scopus 로고
    • Unmasking multivariate outliers and leverage points
    • Rousseeuw P and Van Zomeren B (1990). Unmasking multivariate outliers and leverage points. J Am Stat Assoc 85(411):633-651
    • (1990) J Am Stat Assoc , vol.85 , Issue.411 , pp. 633-651
    • Rousseeuw, P.1    Van Zomeren, B.2
  • 21
    • 33845240405 scopus 로고    scopus 로고
    • Capabilities of outlier detection schemes in large datasets, framework and methodologies
    • Tang J, Chen J, Fu A and Cheung W (2007). Capabilities of outlier detection schemes in large datasets, framework and methodologies. Knowl Inf Syst 11(1):45-84
    • (2007) Knowl Inf Syst , vol.11 , Issue.1 , pp. 45-84
    • Tang, J.1    Chen, J.2    Fu, A.3    Cheung, W.4
  • 22
    • 32544438259 scopus 로고    scopus 로고
    • On efficiently summarizing categorical databases
    • Wang J and Karypis G (2006). On efficiently summarizing categorical databases. Knowl Inf Syst 9(1):19-37
    • (2006) Knowl Inf Syst , vol.9 , Issue.1 , pp. 19-37
    • Wang, J.1    Karypis, G.2
  • 23
    • 13844297591 scopus 로고    scopus 로고
    • HARP: A practical projected clustering algorithm
    • Yip K, Cheung D and Ng M (2004). HARP: A practical projected clustering algorithm. IEEE Trans Knowl Data Eng 16(11):1387-1397
    • (2004) IEEE Trans Knowl Data Eng , vol.16 , Issue.11 , pp. 1387-1397
    • Yip, K.1    Cheung, D.2    Ng, M.3
  • 25
    • 14644404956 scopus 로고    scopus 로고
    • Frequent-pattern based iterative projected clustering
    • Yiu M and Mamoulis N (2005). Frequent-pattern based iterative projected clustering. IEEE Trans Knowl Data Eng 17(2):176-189
    • (2005) IEEE Trans Knowl Data Eng , vol.17 , Issue.2 , pp. 176-189
    • Yiu, M.1    Mamoulis, N.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.