Abstract：To enhance the efficiency of lag correlation sequences mining for big data stream, a lag correlation mining method based on Boolean reduction and layered series is proposed in this paper. Firstly, by two sequence averages of the original data stream, the big data stream sequence is transformed by the improved Boolean to effectively decrease the computational cost of Boolean reduction. Secondly, through conversion and reduction of sequence elements, the number of the sequence element is reduced. And the proposed method overcomes the drawback of the traditional algorithm in computing lag correlations of all sequence elements. The experiments show the effective reduction in computational time and obvious improvement in computational accuracy of the proposed method.
任永功，钱海振，郎泓钰. 基于改进布尔约减级数分层的大数据流滞后相关性挖掘方法*[J]. 模式识别与人工智能, 2016, 29(5): 455-463.
REN Yonggong, QIAN Haizhen, LANG Hongyu. Lag Correlation Mining Method Based on Improved Boolean Reduction and Layered Series for Big Data Stream. , 2016, 29(5): 455-463.
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