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Volumn , Issue , 2009, Pages 43-52

An improved frequent pattern-growth approach to discover rare association rules

Author keywords

Data mining; Frequent patterns; Rare association rules; Rare knowledge patterns

Indexed keywords

APRIORI; CANDIDATE PATTERNS; DATA SETS; FREQUENT PATTERNS; MINIMUM SUPPORT; MULTIPLE MINIMUM SUPPORTS; NODE PRUNING; PERFORMANCE PROBLEMS; RARE ASSOCIATION RULES; REAL-WORLD DATASETS;

EID: 77955403557     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (16)

References (12)
  • 10
    • 4243998561 scopus 로고
    • Computer systems that learn: Classification and prediction models from statistics
    • Morgan Kaufmann
    • Weiss, S. and Kulikowski, C. A. (1991). Computer systems that learn: Classification and prediction models from statistics. In Neural Nets, Machine Learning, and Expert Systems. Morgan Kaufmann.
    • (1991) Neural Nets, Machine Learning, and Expert Systems
    • Weiss, S.1    Kulikowski, C.A.2
  • 12
    • 77955385813 scopus 로고    scopus 로고
    • Mining association rules with multiple minimum supports: A new algorithm and a support tuning mechanism
    • Ya-Han Hu, Y.-L. C. (2004). Mining association rules with multiple minimum supports: A new algorithm and a support tuning mechanism. In Decision Support Systems.
    • (2004) Decision Support Systems
    • Hu, Y.-H.1    C, Y.-L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.