Frequent itemset mining (FIM) is an essential part of association rules mining. Its application for other data mining tasks has also been recognized. It has been an active researc...
Mining frequent patterns on streaming data is a new challenging problem for the data mining community since data arrives sequentially in the form of continuous rapid streams. In t...
Abstract In this paper we propose a novel parallel algorithm for frequent itemset mining. The algorithm is based on the filter-stream programming model, in which the frequent item...
Adriano Veloso, Wagner Meira Jr., Renato Ferreira,...
Most approaches to mining association rules implicitly consider the utilities of the itemsets to be equal. We assume that the utilities of itemsets may differ, and identify the hi...