EMIS ELibM Electronic Journals Publications de l'Institut Mathématique, Nouvelle Série
Vol. 87(101), pp. 109–119 (2010)

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AN EFFICIENT PROCEDURE FOR MINING STATISTICALLY SIGNIFICANT FREQUENT ITEMSETS

Predrag Stanisic and Savo Tomovic

Department of Mathematics and Computer Science, University of Montenegro, Podgorica, Montenegro

Abstract: We suggest the original procedure for frequent itemsets generation, which is more efficient than the appropriate procedure of the well known Apriori algorithm. The correctness of the procedure is based on a special structure called Rymon tree. For its implementation, we suggest a modified sort-merge-join algorithm. Finally, we explain how the support measure, which is used in Apriori algorithm, gives statistically significant frequent itemsets.

Keywords: data mining, knowledge discovery in databases, association analysis, Apriori algorithm

Classification (MSC2000): 03B70; 68T27, 68Q17

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Electronic fulltext finalized on: 20 Apr 2010. This page was last modified: 18 Jan 2016.

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