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Volumn 4203 LNAI, Issue , 2006, Pages 473-482

A new clustering approach for symbolic data and its validation: Application to the healthcare data

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COLOR; COMPUTATIONAL GEOMETRY; GRAPH THEORY;

EID: 33750317900     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11875604_54     Document Type: Conference Paper
Times cited : (25)

References (9)
  • 2
    • 0032091595 scopus 로고    scopus 로고
    • CURE: An efficient clustering algorithm for large databases
    • Seattle, WA
    • Guha, S., R. Rastogi, and K. Shim. CURE: An efficient clustering algorithm for large databases. In Proceedings of the ACM SIGMOD Conference, Seattle, WA, pages 73-84, 1998.
    • (1998) Proceedings of the ACM SIGMOD Conference , pp. 73-84
    • Guha, S.1    Rastogi, R.2    Shim, K.3
  • 3
    • 0004173623 scopus 로고
    • Efficient algorithms for divisive hierarchical clustering with the diameter criterion
    • Guénoche, A., P. Hansen, and B. Jaumard. Efficient algorithms for divisive hierarchical clustering with the diameter criterion. Journal of Classification, volume. 8, pages 5-30, 1991.
    • (1991) Journal of Classification , vol.8 , pp. 5-30
    • Guénoche, A.1    Hansen, P.2    Jaumard, B.3
  • 4
    • 0001138328 scopus 로고
    • Algorithm AS136: A k-means clustering algorithm
    • Hartigan, J. and M. Wong. Algorithm AS136: A k-means clustering algorithm. Journal of Applied Statistics, volume 28, pages 100-108, 1979.
    • (1979) Journal of Applied Statistics , vol.28 , pp. 100-108
    • Hartigan, J.1    Wong, M.2
  • 5
    • 0003136237 scopus 로고
    • Efficient and effective clustering methods for spatial data mining
    • Santiago, Chile
    • NG, R. and J. HAN. Efficient and effective clustering methods for spatial data mining. In Proceedings of the 20th Conference on VLDB, Santiago, Chile, pages 144-155, 1994.
    • (1994) Proceedings of the 20th Conference on VLDB , pp. 144-155
    • Ng, R.1    Han, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.