Pattern Discovery for Locating Motifs in Multivariate, Real-valued Time-series Data
نویسندگان
چکیده
The problem of locating motifs in multivariate, real-valued time series data concerns the discovery of sets of recurring patterns embedded in the time series. Each set is composed of several nonoverlapping subsequences and constitutes a motif because all of the subsequences are similar. This task is a natural extension of univariate motif discovery in both the symbolic and real-valued domains as previously addressed in the bioinformatics and data-mining research.
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تاریخ انتشار 2007