中文摘要：

在频繁模式挖掘（FPM）的研究中，为了在海量数据流中有效地挖掘子树结构的频繁模式，根据数据流和子树模式的特点，提出了一种基于数据流的频繁标记闭子树挖掘（SFCL Tree Miner）算法．该算法首次对动态数据流中频繁标记闭子树的挖掘进行研究，给出了在数据流中标记闭子树集合添加、删除的批量挖掘方法，并结合时间衰减模型，有效保证了结果的时效性．实验结果表明，该算法在挖掘性能，如挖掘时间和内存占用等方面，比类似算法有较大提高．

英文摘要：

Compared with the classic frequent pattern mining （FPM） algorithms, the dynamic FPM algo- rithms on fast and massive data streams have become top research nowadays. A new batch mining algo-rithm in data streams called stream frequent closed labeled tree miner （SFCLTreeMiner） is proposed. SFCLTreeMiner uses a kind of adding-removing method between closed tree sets. Also it provides a time decay module for reasonable data updating. Experiment shows that SFCLTreeMiner is efficient in data streams mining by reducing consuming dramatically.