Finding patterns/motifs in time series data

From ISLAB/CAISR
Title Finding patterns/motifs in time series data
Summary Finding patterns/motifs in time series data, for autonomous clustering or outlier detection
Keywords
TimeFrame
References
Prerequisites
Author
Supervisor Thorsteinn Rögnvaldsson, Mohamed-Rafik Bouguelia
Level Master
Status Draft


The goal of this project is to find patterns/motifs in time series data. This can be applied for the purpose of autonomous clustering (to explore the data and better understand how a system works) or for the purpose of outlier detection (e.g. to detect faults in a given system).