Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …

We present a comprehensive, detailed review of time-series data analysis, with emphasis on
deep time-series clustering (DTSC), and a case study in the context of movement behavior …

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 …

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 …

Time series clustering is an active research area with applications in a wide range of fields.
One key component in cluster analysis is determining a proper dissimilarity measure …

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 …

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 …

The previous decade has brought a remarkable increase of the interest in applications that
deal with querying and mining of time series data. Many of the research efforts in this context …

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 …