A Fast On-Line ϵ-Approximation Algorithm for Mining Strongly Closed Itemsets

In this paper, we give a novel on-line ϵ-approximation algorithm for mining the set of strongly closed itemsets in a transaction stream, and also study its acceleration technique with several pruning methods such as look-ahead success detection for strongly closed itemsets. We also show some experimental results for evaluating the proposed algorithms.