Time series are the primary data type used to record dynamic system measurements and
generated in great volume by both physical sensors and online processes (virtual sensors) …

Time series is an important class of temporal data objects and it can be easily obtained from
scientific and financial applications. A time series is a collection of observations made …

We propose a simple but strong baseline for time series classification from scratch with deep
neural networks. Our proposed baseline models are pure end-to-end without any heavy …

This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …

As computers become more pervasive in society, facilitating natural human–computer
interaction (HCI) will have a positive impact on their use. Hence, there has been growing …

Time series has wide applications in the real world and is known to be difficult to forecast.
Since its statistical properties change over time, its distribution also changes temporally …

The monograph Data Clustering: Theory, Algorithms, and Applications was published in
2007. Starting with the common ground and knowledge for data clustering, the monograph …

The proliferation and ubiquity of temporal data across many disciplines has generated
substantial interest in the analysis and mining of time series. Clustering is one of the most …

Abstract Dynamic Time War** (DTW) has a quadratic time and space complexity that limits
its use to small time series. In this paper we introduce FastDTW, an approximation of DTW …

In almost every scientific field, measurements are performed over time. These observations
lead to a collection of organized data called time series. The purpose of time-series data …