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...
Standard algorithms for association rule mining are based on identification of frequent itemsets. In this paper, we study how to maintain privacy in distributed mining of frequen...
Computing frequent itemsets is one of the most prominent problems in data mining. We study the following related problem, called FREQSAT, in depth: given some itemset-interval pai...
Itemset share has been proposed as a measure of the importance of itemsets for mining association rules. The value of the itemset share can provide useful information such as total...
In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data ...