A new approach for mining top-rank-k erasable itemsets

Abstract

Erasable itemset mining first introduced in 2009 is an interesting variation of pattern mining. The managers can use the erasable itemsets for planning production plan of the factory. Besides the problem of mining erasable itemsets, the problem of mining top-rank-k erasable itemsets is an interesting and practical problem. In this paper, we first propose a new structure, call dPID-List and two theorems associated with it. Then, an improved algorithm for mining top-rank-k erasable itemsets using dPID-List structure is developed. The effectiveness of the proposed method has been demonstrated by comparisons in terms of mining time and memory usage with VM algorithm for three datasets. © 2014 Springer International Publishing Switzerland.