We present a generalization of frequent itemsets allowing the notion of errors in the itemset definition. We motivate the problem and present an efficient algorithm that identifie...
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
Abstract. In this paper, we propose a novel mining task: mining frequent superset from the database of itemsets that is useful in bioinformatics, e-learning systems, jobshop schedu...
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...
Association rule mining (ARM) identifies frequent itemsets from databases and generates association rules by assuming that all items have the same significance and frequency of oc...