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Volumn 1704, Issue , 1999, Pages 204-213

Optimizing disjunctive association rules

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATION RULES;

EID: 78149342941     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-48247-5_22     Document Type: Conference Paper
Times cited : (2)

References (14)
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    • Agrawal, R.1    Imielinski, T.2    Swami, A.3
  • 4
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    • Mining optimized association rules for numeric attributes
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  • 6
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    • Gunopoulos, D.1    Mannila, H.2    Saluja, S.3
  • 7
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    • Data mining, hypergraph transversals, and machine learning (Extended abstract)
    • D. Gunopulos, H. Mannila, R. Khardon, and H. Toivonen. Data mining, hypergraph transversals, and machine learning (extended abstract). In PODS, 1997.
    • (1997) PODS
    • Gunopulos, D.1    Mannila, H.2    Khardon, R.3    Toivonen, H.4
  • 8
    • 0003343155 scopus 로고
    • Discovery of multiple-level association rules from large databases
    • J. Han and Y. Fu. Discovery of multiple-level association rules from large databases. In VLDB, 1995.
    • (1995) VLDB
    • Han, J.1    Fu, Y.2
  • 10
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    • Fast approximation algorithms for knapsack problems
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    • (1979) Mathematics of Operations Research , pp. 4
    • Lawler, E.1
  • 11
    • 0001280495 scopus 로고
    • Efficient algorithms for discovering association rules
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    • (1994) KDD
    • Mannila, H.1    Toivonen, H.2    Verkamo, A.I.3
  • 12
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    • Mining optimized association rules for categorical and numeric attributes
    • R. Rastogi and K. Shim. Mining optimized association rules for categorical and numeric attributes. In ICDE, 1998.
    • (1998) ICDE
    • Rastogi, R.1    Shim, K.2
  • 13
    • 0030157416 scopus 로고    scopus 로고
    • Mining quantitative association rules in large relational tables
    • R. Srikant and R. Agrawal. Mining quantitative association rules in large relational tables. In ICMD, 1996.
    • (1996) ICMD
    • Srikant, R.1    Agrawal, R.2
  • 14
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    • An efficient algorithm for mining association rules in large databases
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.