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Volumn 2637, Issue , 2003, Pages 75-87

Automatic extraction of clusters from hierarchical clustering representations1

Author keywords

Dendrogram; Hierarchical clustering; OPTICS; Reachability plot; Single Link method

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; LEARNING SYSTEMS; DATA MINING; HIERARCHICAL SYSTEMS; OPTICS;

EID: 7444230467     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/3-540-36175-8_8     Document Type: Conference Paper
Times cited : (109)

References (10)
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    • Ankerst M., Breunig M. M., Kriegel H.-P., Sander J.: "OPTICS: Ordering Points To Identify the Clustering Structure", Proc. ACM SIGMOD, Philadelphia, PA, 1999, pp 49-60.
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    • Ankerst, M.1    Breunig, M.M.2    Kriegel, H.-P.3    Sander, J.4
  • 2
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    • A density-based algorithm for discovering clusters in large spatial databases with noise
    • Portland, OR
    • Ester M., Kriegel H.-P., Sander J., Xu X.: "A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise", Proc. KDD'96, Portland, OR, 1996, pp. 226-231.
    • (1996) Proc. KDD'96 , pp. 226-231
    • Ester, M.1    Kriegel, H.-P.2    Sander, J.3    Xu, X.4
  • 3
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    • An efficient approach to clustering in large multimedia databases with noise
    • New York City, NY
    • Hinneburg A., Keim D.: "An Efficient Approach to Clustering in Large Multimedia Databases with Noise", KDD'98, New York City, NY, 1998.
    • (1998) KDD'98
    • Hinneburg, A.1    Keim, D.2
  • 5
    • 0030383106 scopus 로고    scopus 로고
    • Finding aggregate proximity relationships and commonalities in spatial data mining
    • December
    • Knorr E. M., Ng R.T.: "Finding Aggregate Proximity Relationships and Commonalities in Spatial Data Mining," IEEE Trans. on Knowledge and Data Engineering, Vol. 8, No. 6, December 1996, pp. 884-897.
    • (1996) IEEE Trans. on Knowledge and Data Engineering , vol.8 , Issue.6 , pp. 884-897
    • Knorr, E.M.1    Ng, R.T.2
  • 7
    • 0001457509 scopus 로고
    • Some methods for classification and analysis of multivariate observations
    • MacQueen J.: "Some Methods for Classification and Analysis of Multivariate Observations", Proc. 5th Berkeley Symp. Math. Statist. Prob., 1967, vol. 1, pp. 281-297.
    • (1967) Proc. 5th Berkeley Symp. Math. Statist. Prob. , vol.1 , pp. 281-297
    • MacQueen, J.1
  • 8
    • 0003136237 scopus 로고
    • Efficient and effective clustering methods for spatial data mining
    • Santiago, Chile, Morgan Kaufmann Publishers, San Francisco, CA
    • Ng R. T., Han J.: "Efficient and Effective Clustering Methods for Spatial Data Mining", Proc. VLDB'94, Santiago, Chile, Morgan Kaufmann Publishers, San Francisco, CA, 1994, pp. 144-155.
    • (1994) Proc. VLDB'94 , pp. 144-155
    • Ng, R.T.1    Han, J.2
  • 9
    • 0003052357 scopus 로고    scopus 로고
    • WaveCluster: A multi-resolution clustering approach for very large spatial databases
    • New York, NY
    • Sheikholeslami G., Chatterjee S., Zhang A.: "WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases", Proc. VLDB'98, New York, NY, 1998, pp. 428-439.
    • (1998) Proc. VLDB'98 , pp. 428-439
    • Sheikholeslami, G.1    Chatterjee, S.2    Zhang, A.3
  • 10
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    • SLINK: An optimally efficient algorithm for the single-link cluster method
    • Sibson R.: "SLINK: an optimally efficient algorithm for the single-link cluster method", The Computer Journal Vol. 16, No. 1, 1973, pp. 30-34.
    • (1973) The Computer Journal , vol.16 , Issue.1 , pp. 30-34
    • Sibson, R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.