Clustering is an essential tool in data mining research and applications. It is the subject of
active research in many fields of study, such as computer science, data science, statistics …

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 …

Drought prediction is an important subject, particularly in drought-hydrology, and has a key
role in risk management, drought readiness and alleviation. Hydrological time series data …

Time series classification is an increasing research topic due to the vast amount of time
series data that is being created over a wide variety of fields. The particularity of the data …

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 …

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 …

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

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 …