Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an associatio...
Abstract. This paper introduces a new algorithm for approximate mining of frequent patterns from streams of transactions using a limited amount of memory. The proposed algorithm co...
Frequent itemsets mining is well explored for various data types, and its computational complexity is well understood. Based on our previous work by Nguyen and Orlowska (2005), th...
We present a depth-first algorithm, PatriciaMine, that discovers all frequent itemsets in a dataset, for a given support threshold. The algorithm is main-memory based and employs...
We consider the problem of publishing sensitive transaction data with privacy preservation. High dimensionality of transaction data poses unique challenges on data privacy and dat...
Yabo Xu, Benjamin C. M. Fung, Ke Wang, Ada Wai-Che...