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Autor:
Zvi M. Kedem, Dao-I Lin
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 14:553-566
Discovering frequent itemsets is a key problem in important data mining applications, such as the discovery of association rules, strong rules, episodes, and minimal keys. Typical algorithms for solving this problem operate in a bottom-up, breadth-fi
Autor:
Dao-I Lin, Zvi M. Kedem
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783540642640
EDBT
EDBT
Discovering frequent itemsets is a key problem in important data mining applications, such as the discovery of association rules, strong rules, episodes, and minimal keys. Typical algorithms for solving this problem operate in a bottom-up breadth-fir
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::28a68ac9a6f9aa40df893f9d1fdee38c
https://doi.org/10.1007/bfb0100980
https://doi.org/10.1007/bfb0100980
Autor:
Dao-I Lin, Kedem, Zvi M.
Publikováno v:
IEEE Transactions on Knowledge & Data Engineering. May/Jun2002, Vol. 14 Issue 3, p553. 14p. 2 Black and White Photographs, 4 Diagrams, 3 Graphs.