A New Rymon Tree Based Procedure for Mining Statistically Significant Frequent Itemsets


  • Predrag Stanisic University of Montenegro Department of Mathematics and Computer Science Dzordza Vasingtona bb, Podgorica, Montenegro
  • Savo Tomovic University of Montenegro Department of Mathematics and Computer Science Dzordza Vasingtona bb, Podgorica, Montenegro


frequent itemset mining, association analysis, Apriori algorithm, Rymon tree


In this paper we suggest a new method for frequent itemsets mining, which is more efficient than well known Apriori algorithm. The method is based on special structure called Rymon tree. For its implementation, we suggest modified sort-merge-join algorithm. Finally, we explain how support measure, which is used in Apriori algorithm, gives statistically significant frequent itemsets.


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