Scalable Analytics on Large Sequence Collections

Karima Echihabi, Themis Palpanas

Abstract: Data series are a prevalent data type that has attracted lots of interest in recent years. Specifically, there has been an explosive interest towards the analysis of large volumes of data series in many different domains, and in particular, in the Internet of Things (IoT). In this tutorial, we focus on applications that produce massive collections of data series, and we provide the necessary background on data series management and analytics. Moreover, we discuss the need for fast similarity search for supporting machine learning applications, and describe efficient similarity search techniques, indexes and query processing algorithms. Finally, we discuss the role that deep learning techniques can play in this context. We conclude with the challenges and open research problems in this domain.