COBRA: Closed Sequential Pattern Mining Using Bi-phase Reduction Approach

摘要

In this work, we study the problem of closed sequential pattern mining. We propose a novel approach which extends a frequent sequence with closed itemsets instead of single items. The motivation is that closed sequential patterns are composed of only closed itemsets. Hence, unnecessary item extensions which generates non-closed sequential patterns can be avoided. Experimental evaluation shows that the proposed approach is two orders of magnitude faster than previous works with a modest memory cost.