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Volumn 1800 LNCS, Issue , 2000, Pages 399-406

Exploiting dataset similarity for distributed mining

Author keywords

[No Author keywords available]

Indexed keywords

DIGITAL STORAGE;

EID: 84876371181     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45591-4_52     Document Type: Conference Paper
Times cited : (8)

References (11)
  • 1
    • 0031649139 scopus 로고    scopus 로고
    • Online generation of association rules
    • C. Aggarwal and P. Yu. Online generation of association rules. In ICDE'98.
    • ICDE'98
    • Aggarwal, C.1    Yu, P.2
  • 4
    • 0001882616 scopus 로고
    • Fast algorithms for mining association rules
    • R. Agrawal and R. Srikant. Fast algorithms for mining association rules. In 20th VLDB Conf., 1994.
    • (1994) 20th VLDB Conf.
    • Agrawal, R.1    Srikant, R.2
  • 6
    • 0030285403 scopus 로고    scopus 로고
    • The KDD process of rextracing useful information from volumes of data
    • U. M. Fayyad, G. Piatetsky-Shapiro, and P. Smyth. The KDD process of rextracing useful information from volumes of data. Communications of ACM, 39(11):27-34, 1996.
    • (1996) Communications of ACM , vol.39 , Issue.11 , pp. 27-34
    • Fayyad, U.M.1    Piatetsky-Shapiro, G.2    Smyth, P.3
  • 9
    • 0038246813 scopus 로고    scopus 로고
    • Defining diff as a data mining primitive
    • R. Subramonian. Defining diff as a data mining primitive. In KDD 1998.
    • (1998) KDD
    • Subramonian, R.1
  • 10
    • 0002663969 scopus 로고    scopus 로고
    • Sampling large databases for association rules
    • H. Toivonen. Sampling large databases for association rules. In VLDB Conf., 1996.
    • (1996) VLDB Conf.
    • Toivonen, H.1
  • 11
    • 85138646379 scopus 로고    scopus 로고
    • New algorithms for fast discovery of association rules
    • M. J. Zaki, S. Parthasarathy, M. Ogihara, and W. Li. New algorithms for fast discovery of association rules. In KDD, 1997.
    • (1997) KDD
    • Zaki, M.J.1    Parthasarathy, S.2    Ogihara, M.3    Li, W.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.