Analyzing closed frequent itemsets with convex polytopes

Computing frequent itemsets in transactional databases is a vital but computationally expensive task. Measuring the difference of two datasets is often done by computing their respective frequent itemsets despite high computational cost. This paper proposes a linear programming-based approach to this problem and shows that there exists a distance measure for transactional database that relies on closed frequent itemsets but does not require their generation.