Mining closed frequent itemsets in the sliding window over data stream

Abstract

Mining closed frequent itemsets in the sliding window is one of important topics of data streams mining. In this paper, we propose an algorithm, MCFI-SW, which mines closed frequent itemsets in the sliding window of data streams efficiently. It uses a CFP-tree based on FP-tree to record the current information in stream and prunes the obsolete items and a lot of infrequent items by operating the pointer. A novel approach is presented to mine a set of closed frequent itemsets in the CFP-tree. Theoretical analysis and experimental results show that the proposed method is efficient and scalable.