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 ...
Discovering association rules by identifying relationships among sets of items in a transaction database is an important problem in Data Mining. Finding frequent itemsets is compu...
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...
- Several algorithms have been introduced for mining frequent itemsets. The recent datasettransformation approach suffers either from the possible increasing in the number of struc...
The paper presents a method for pruning frequent itemsets based on background knowledge represented by a Bayesian network. The interestingness of an itemset is defined as the abso...