HashMax: A New Method for Mining Maximal Frequent Itemsets

Mining maximal frequent itemsets is a fundamental problem in many data mining applications, especially in the case of dense data when the search space is exponential. We propose a top-down algorithm that employs hashing techniques, named HashMax, in order to generate maximal frequent itemsets efficiently. An empirical evaluation of our algorithm in comparison with the state-of-the-art maximal frequent itemset generation algorithm Genmax shows the advantage of HashMax in the case of dense datasets with a large amount of maximal