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Visual exploration of frequent patterns in multivariate time series
2012
Information Visualization
The detection of frequently occurring patterns, also called motifs, in data streams has been recognized as an important task. To find these motifs, we use an advanced event encoding and pattern discovery algorithm. Since a large time series can contain hundreds of motifs, there is a need to support interactive analysis and exploration. In addition, for certain applications, such as data center resource management, service managers want to be able to predict the next day's power consumption from
doi:10.1177/1473871611430769
fatcat:xsxorbfbg5fn3iijpmu6kks7z4