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Volumn 25, Issue 2, 1996, Pages 103-114

BIRCH: An Efficient Data Clustering Method for Very Large Databases

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DATA PROCESSING; HIERARCHICAL SYSTEMS;

EID: 0030157145     PISSN: 01635808     EISSN: None     Source Type: Journal    
DOI: 10.1145/235968.233324     Document Type: Article
Times cited : (4243)

References (15)
  • 3
    • 0019280022 scopus 로고
    • Clustering Methodologies in Exploratory Data Analysis
    • Edited by M.C. Yovits, Academic Press, New York
    • R. Dubes, and A.K. Jain, Clustering Methodologies in Exploratory Data Analysis Advances in Computers, Edited by M.C. Yovits, Vol. 19, Academic Press, New York, 1980.
    • (1980) Advances in Computers , vol.19
    • Dubes, R.1    Jain, A.K.2
  • 5
    • 0002382156 scopus 로고
    • Knowledge Discovery in Large Spatial Databases: Focusing Techniques for Efficient Class Identification
    • Portland, Maine, U.S.A.
    • Martin Ester, Hans-Peter Kriegel, and Xiaowei Xu, Knowledge Discovery in Large Spatial Databases: Focusing Techniques for Efficient Class Identification, Proc. of 4th Int'l Symposium on Large Spatial Databases, Portland, Maine, U.S.A., 1995.
    • (1995) Proc. of 4th Int'l Symposium on Large Spatial Databases
    • Ester, M.1    Kriegel, H.-P.2    Xu, X.3
  • 6
    • 0343442766 scopus 로고
    • Knowledge Acquisition via Incremental Conceptual Clustering
    • Douglas H. Fisher, Knowledge Acquisition via Incremental Conceptual Clustering, Machine Learning, 2(2), 1987
    • (1987) Machine Learning , vol.2 , Issue.2
    • Fisher, D.H.1
  • 7
    • 0012904409 scopus 로고    scopus 로고
    • Iterative Optimization and Simplification of Hierarchical Clusterings
    • Dept. of Computer Science, Vanderbilt University, Nashville, TN 37235
    • Douglas H. Fisher, Iterative Optimization and Simplification of Hierarchical Clusterings, Technical Report CS-95-01, Dept. of Computer Science, Vanderbilt University, Nashville, TN 37235.
    • Technical Report CS-95-01
    • Fisher, D.H.1
  • 10
    • 0000166613 scopus 로고
    • Experiments with Incremental Concept Formation : UNIMEM
    • Michael Lebowitz, Experiments with Incremental Concept Formation : UNIMEM, Machine Learning, 1987.
    • (1987) Machine Learning
    • Lebowitz, M.1
  • 11
    • 0010155698 scopus 로고
    • Clustering analysis and its applications
    • Edited by J.T. Toum, Plenum Press, New York
    • R.C.T. Lee, Clustering analysis and its applications, Advances in Information Systems Science, Edited by J.T. Toum, Vol. 8, pp. 169-292, Plenum Press, New York, 1981.
    • (1981) Advances in Information Systems Science , vol.8 , pp. 169-292
    • Lee, R.C.T.1
  • 12
    • 0020848951 scopus 로고
    • A Survey of Recent Advances in Hierarchical Clustering Algorithms
    • F. Murtagh, A Survey of Recent Advances in Hierarchical Clustering Algorithms, The Computer Journal, 1983.
    • (1983) The Computer Journal
    • Murtagh, F.1
  • 13
    • 0003136237 scopus 로고
    • Efficient and Effective Clustering Methods for Spatial Data Mining
    • Raymond T. Ng and Jiawei Han, Efficient and Effective Clustering Methods for Spatial Data Mining, Proc. of VLDB, 1994.
    • (1994) Proc. of VLDB
    • Ng, R.T.1    Han, J.2
  • 14
    • 0005389587 scopus 로고
    • Parallel Algorithms for Hierarchical Clustering
    • Computer Science Division, Univ. of California at Berkeley, Dec.
    • Clark F. Olson, Parallel Algorithms for Hierarchical Clustering, Technical Report, Computer Science Division, Univ. of California at Berkeley, Dec.,1993.
    • (1993) Technical Report
    • Olson, C.F.1
  • 15
    • 0343820198 scopus 로고
    • BIRCH: An Efficient Data Clustering Method for Very Large Databases
    • Computer Sciences Dept., Univ. of Wisconsin-Madison
    • Tian Zhang, Raghu Ramakrishnan, and Miron Livny, BIRCH: An Efficient Data Clustering Method for Very Large Databases, Technical Report, Computer Sciences Dept., Univ. of Wisconsin-Madison, 1995.
    • (1995) Technical Report
    • Zhang, T.1    Ramakrishnan, R.2    Livny, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.