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Volumn 20, Issue 10, 2005, Pages 1077-1089

Scalable algorithms for clustering large datasets with mixed type attributes

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; NUMERICAL ANALYSIS;

EID: 27844433509     PISSN: 08848173     EISSN: None     Source Type: Journal    
DOI: 10.1002/int.20108     Document Type: Article
Times cited : (60)

References (22)
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    • Zhang, T.1    Ramakishnan, R.2    Livny, M.3
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    • WaveCluster: A multi-resolution clustering approach for very large spatial databases
    • New York. San Francisco, CA: Morgan Kaufmann
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    • (1998) Proc 1998 Int Conf on Very Large Databases , pp. 428-439
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    • New York. San Francisco, CA: Morgan Kaufmann
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    • (1998) Proc 1998 Int Conf on Very Large Databases (VLDB'98) , pp. 311-323
    • Gibson, D.1    Kleiberg, J.2    Raghavan, P.3
  • 13
    • 13444273324 scopus 로고    scopus 로고
    • A cluster ensemble method for clustering categorical data
    • He Z, Xu X, Deng S. A cluster ensemble method for clustering categorical data. Inform Fusion 2005 ;6 (2): 143-151.
    • (2005) Inform Fusion , vol.6 , Issue.2 , pp. 143-151
    • He, Z.1    Xu, X.2    Deng, S.3
  • 15
    • 27144536001 scopus 로고    scopus 로고
    • Extensions to the k-means algorithm for clustering large data sets with categorical values
    • Huang Z. Extensions to the k-means algorithm for clustering large data sets with categorical values. Data Min Knowl Discov 1998;2:283-304.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.