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Volumn 110, Issue , 2004, Pages 430-434

Statistical strategies for pruning all the uninteresting association rules ?

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DISTRIBUTION FUNCTIONS;

EID: 85017405682     PISSN: 09226389     EISSN: 18798314     Source Type: Book Series    
DOI: None     Document Type: Conference Paper
Times cited : (5)

References (13)
  • 4
    • 4944260909 scopus 로고    scopus 로고
    • Vila measuring the accuracy and interest of association rules: A new framework
    • F. Berzal, I. Blanco, D. Sanchez and María-Amparo Vila Measuring the Accuracy and Interest of Association Rules: A new Framework. Journal Intelligent Data Analysis, Vol 6, pages 221-235. 2002.
    • (2002) Journal Intelligent Data Analysis , vol.6 , pp. 221-235
    • Berzal, F.1    Blanco, I.2    Sanchez, D.3    María-Amparo4
  • 6
    • 0031162961 scopus 로고    scopus 로고
    • Dynamic itemset counting and implication rules for market basket data
    • S. Brin, R. Motwani, J. Ullman, and S. Tsur. Dynamic Itemset Counting and Implication Rules for Market Basket Data. Proc. Int'l Conf. on Management of Data, Volume 6:2, 255 - 264. 1997.
    • (1997) Proc. Int'l Conf. on Management of Data , vol.6 , Issue.2 , pp. 255-264
    • Brin, S.1    Motwani, R.2    Ullman, J.3    Tsur, S.4
  • 7
    • 78149312575 scopus 로고    scopus 로고
    • Genearating an informative cover for association rules
    • L. Cristofor, and D. Simovici. Genearating an Informative Cover for Association Rules. Int'l Conf. on Data Mining, p.597. 2002.
    • (2002) Int'l Conf. on Data Mining , pp. 597
    • Cristofor, L.1    Simovici, D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.