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 …

Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …

Data-driven intelligent transportation systems utilize data resources generated within
intelligent systems to improve the performance of transportation systems and provide …

Visual analytics systems combine machine learning or other analytic techniques with
interactive data visualization to promote sensemaking and analytical reasoning. It is through …

Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data.
For DR techniques to be useful in exploratory data analysis, they need to be adapted to …

While many VA workflows make use of machine-learned models to support analytical tasks,
VA workflows have become increasingly important in understanding and improving Machine …

In this paper, we present an interactive visual analytics system, Triple Perspective Visual
Trajectory Analytics (TripVista), for exploring and analyzing complex traffic trajectory data …

This paper comprehensively surveys the development of trajectory clustering. Considering
the critical role of trajectory data mining in modern intelligent systems for surveillance …

One of the most common operations in exploration and analysis of various kinds of data is
clustering, ie discovery and interpretation of groups of objects having similar properties …

Visual analytics for time series data has received a considerable amount of attention.
Different approaches have been developed to understand the characteristics of the data and …