A Novel Approach for Mining Multiple Data Streams Based on Lag Correlation

摘要：

Correlation analysis is a key problem for data stream analysis. In this paper, we propose a correlation analysis method for multiple dimensional data streams, which is based on the Boolean lag representation and the PCA (Principal Component Analysis). Firstly, the raw stream sequence is transformed into the Boolean sequence. By the correlation analysis of Boolean sequences, we can easily find the sequence pairs with lag correlations by means of simple bit operations. Secondly, we compute the lag time and synchronize the multiple dimensional data stream. Thirdly, the PCA method is deployed to reduce the multiple data streams, and we can reconstruct the data streams by a few principal components. The experimental evaluations show that the method has high computation performance with high accuracy.

关键词： data stream Boolean lag correlation PCA

作者: Tiancheng Zhang Dejun Yue Yanqiu wang Ge Yu

作者单位: College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, China, 110819

会议类型: 国际会议

会议名称: 2011 China Control and Decision Conference(2011中国控制与决策会议 CCDC)

会议地点: 四川绵阳

会议语种:英文

页码: 2382-2387

在线出版日期: 2011-05-23（万方平台首次上网日期，不代表论文的发表时间）