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A Brief Survey on Techniques Used in Discovering Time Series Motifs

Time series data are set of observations collected on equal time intervals in applications of different domains like medicine, motion-capture, seismology, sensor networks, telecommunication, etc. Time series motifs are time sub-sequences data, occurring repeatedly in an application and are unknown in advance. Motifs are useful in retrieving information from time series databases using data mining techniques. Discovering time series motifs in time series data is an important task before applying a data mining technique. In literature, several algorithms have been proposed to increase the efficiency and accuracy for time series motifs discovery. This paper presents a brief survey on techniques used in discovering time series motifs.