在线挖掘数据流滑动窗口中频繁闭项集

Abstract

Abstract: Online mining closed frequent itemsets in sliding window is one of the most important issues for mining data streams.A novel algorithm,FPCFI-DS,is proposed,which can efficiently mine closed frequent itemsets over a stream sliding window with limited memory space,and maintain exact closed frequent itemsets in current window at any time.For data in the first window,the algorithm FPCFI-DS mines closed frequent itemsets using single-pass procedure,denoted as FPCFI.The resulting closed frequent itemsets are stored in a global closed frequent itemsets tree(GCT).When the window slides forward,the FPCFI-DS quickly updates closed frequent itemsets in current window using the updating-mining method.The experimental results show that FPCFI-DS is superior to that of state-of-the-art algorithm Moment in terms of time and space efficiency.

CLC Number:

TP311

AO Fu-jiang, DU Jing, YAN Yue-jin, HUANG Ke-di. Online mining closed frequent itemsets over a stream sliding window[J]. Journal of Systems Engineering and Electronics, 2009, 31(5): 1235-1240.

References

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Online mining closed frequent itemsets over a stream sliding window

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