DocumentCode :
3306026
Title :
Mining free itemsets under constraints
Author :
Boulicaut, Jean-François ; Jeudy, Baptiste
Author_Institution :
Lab. d´´Ingenierie des Syst. d´´Inf., Inst. Nat. des Sci. Appliquees de Lyon, Villeurbanne, France
fYear :
2001
fDate :
2001
Firstpage :
322
Lastpage :
329
Abstract :
Computing frequent itemsets and their frequencies from large Boolean matrices (e.g., to derive association rules) has been one of the hot topics in data mining. Levelwise algorithms (e.g., the a priori algorithm) have been proved effective for frequent itemset mining from sparse data. However, in many practical applications, the computation turns out to be intractable for the user-given frequency threshold and the lack of focus leads to huge collections of frequent itemsets. In the last three years, two promising issues have been investigated: the use of user defined constraints and closed set mining. To the best of our knowledge, combining these two frameworks has not been studied yet. The authors show that the benefit of these two approaches can be combined into levelwise algorithms. An experimental validation related to the discovery of association rules with negations is reported
Keywords :
associative processing; computability; constraint handling; data mining; database theory; transaction processing; very large databases; a priori algorithm; association rules; closed set mining; constraints; data mining; experimental validation; free itemset mining; frequent itemset mining; frequent itemsets; large Boolean matrices; levelwise algorithms; negations; practical applications; sparse data; user defined constraints; user-given frequency threshold; Association rules; Computer applications; Data mining; Frequency; Itemsets; Prototypes; Sparse matrices; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Database Engineering and Applications, 2001 International Symposium on.
Conference_Location :
Grenoble
Print_ISBN :
0-7695-1140-6
Type :
conf
DOI :
10.1109/IDEAS.2001.938100
Filename :
938100
Link To Document :
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