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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.