The increasing availability of vehicular trajectory data is at the core of smart mobility
solutions. Such data offer us unprecedented information for the development of trajectory …

Clustering of big data has received much attention recently. In this paper, we present a new
clusiVAT algorithm and compare it with four other popular data clustering algorithms. Three …

Recently, a new density-peak-based clustering method, called clustering with local density
peaks-based minimum spanning tree (LDP-MST), was proposed, which has several …

Clustering large volumes of high-dimensional data is a challenging task. Many clustering
algorithms have been developed to address either handling datasets with a very large …

Clustering of large-scale vehicle trajectories is an important aspect for understanding urban
traffic patterns, particularly for optimizing public transport routes and frequencies and …

This paper proposes a novel application of Visual Assessment of Tendency (VAT)-based
hierarchical clustering algorithms (VAT, iVAT, and clusiVAT) for trajectory analysis. We …

Exploratory data analysis (EDA) using data clustering is extremely important for
understanding the basic characteristics of a novel data set before developing complex …

Visual methods were used for pre-cluster assessment and useful cluster partitions. Existing
visual methods, such as visual assessment tendency (VAT), spectral VAT (SpecVAT), cosine …

Clustering tendency assessment, which aims to deduce if a dataset contains any cluster
structure, and, if it does, how many clusters it has, is a critical problem in exploratory data …

The growth in pervasive network infrastructure called the Internet of Things (IoT) enables a
wide range of physical objects and environments to be monitored in fine spatial and …