This paper explores the generation of candidates, which is an important step in frequent itemset mining algorithms, from a theoretical point of view. Important notions in our prob...
This work proposes a theoretical guideline in the specific area of Frequent Itemset Mining (FIM). It supports the hypothesis that the use of neural network technology for the prob...
A simple new algorithm is suggested for frequent itemset mining, using item probabilities as the basis for generating candidates. The method first finds all the frequent items, an...
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...
In this paper, we consider a novel scheme referred to as Cartesian contour to concisely represent the collection of frequent itemsets. Different from the existing works, this sche...