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

AN EFFICIENT PROCEDURE FOR MINING STATISTICALLY SIGNIFICANT FREQUENT ITEMSETSPredrag Stanisic and Savo TomovicDepartment of Mathematics and Computer Science, University of Montenegro, Podgorica, MontenegroAbstract: 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 sortmergejoin 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 Full text of the article: (for faster download, first choose a mirror)
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