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Volumn 39, Issue 8, 2006, Pages 1473-1480

An efficient clustering scheme using support vector methods

Author keywords

Clustering; R* tree; Support vector machines

Indexed keywords

DATA STRUCTURES; LEARNING SYSTEMS; OPTIMIZATION; PARAMETER ESTIMATION; PROBLEM SOLVING;

EID: 33646407316     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2006.03.012     Document Type: Article
Times cited : (16)

References (8)
  • 4
    • 33646423628 scopus 로고    scopus 로고
    • J.C. Platt, Fast training of support vector machines using sequential minimum optimization, in: B. Scholkpf, C. Burges, A. Smola (Eds.), Advances in kernel Methods-Support Vector Learning, MIT Press, 1999, pp. 185-208.
  • 6
    • 33646400098 scopus 로고    scopus 로고
    • C.-C. Chang, C.-J. Lin, LIBSVM: a library for support vector machines, 2001.
  • 7
    • 33646428745 scopus 로고    scopus 로고
    • M. Ester, H.-P. Kriegel, J. Sander, X. Xu, A density-based algorithm for discovering clusters in large spatial databases with noise, in: Proceedings of Second International Conference on Knowledge Discovery and Data Mining (KDD-96), 1996, pp. 226-231.
  • 8
    • 33646396557 scopus 로고    scopus 로고
    • P.S. Bradley, U. Fayyad, C. Reinar, Scaling clustering algorithms to large databases, in: Proceedings of Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), AAAI Press, 1998, pp. 9-15.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.