The discovery of time series motifs and discords is considered a paramount and challenging
problem regarding time series analysis. In this work, we present ScrimpCo, a heterogeneous …

Time series analysis is an important research topic of great interest in many fields. Recently,
the Matrix Profile method, and particularly one of its implementations—the SCRIMP …

With the fast digitalization of our society, mining patterns from large time series data is
increasingly becoming a critical problem for a wide range of big data applications. Motif and …

Two fundamental tasks in time series analysis are identifying anomalous events (“discords”)
and repeated patterns (“motifs”). Successfully accomplishing these tasks is of the utmost …

A time series is a chronologically ordered set of samples of a real-valued variable that can
contain millions of observations. Time series analysis is used to analyze information in a …

The recent proposal of the Matrix Profile (MP) has brought the attention of the time series
community to the usefulness and versatility of the similarity joins. This primitive has …

Time series analysis is an important research topic and a key step in monitoring and
predicting events in many fields. Recently, the Matrix Profile method, and particularly two of …

The Dynamic Time Warping (DTW) algorithm is widely used in finding the global alignment
of time series. Many time series data mining and analytical problems can be solved by the …

Time series analysis is an important research topic and a key step in monitoring and
predicting events in many fields. Recently, the Matrix Profile method, and particularly two of …

Time series data remains a perennially important datatype considered in data mining. In the
last decade there has been an increasing realization that time series data can be best …