中文摘要：

由于流数据的流动性与连续性，传统的频繁模式挖掘算法不能直接应用于数据流频繁模式挖掘．挖掘数据流上最近的频繁模式算法使用模式树RFP—tree增量维护数据流上最近的频繁模式，且仅需单次扫描流数据；另外，保守计算策略保证模式挖掘的正确性．仿真试验结果显示，该算法的效率优于其它同类算法．

英文摘要：

Because of the fluidity and continuity of the stream data, the mining algorithms over static databases can not be directly ap- plied to data streams. The algorithm for mining the recent frequent patterns over an online data stream uses RFP-tree to compactly store the recent frequent patterns of a stream by scanning the stream only once. Additionally, the strategy of conservative computation could make sure the correctness of the mining results. Finally, the performance results of simulation show that the algorithra is superior to other analogous algorithms.