Community detection, a fundamental task for network analysis, aims to partition a network
into multiple sub-structures to help reveal their latent functions. Community detection has …

The modern science of networks has made significant advancement in the modeling of
complex real-world systems. One of the most important features in these networks is the …

With the rapid development of information technologies, various big graphs are prevalent in
many real applications (eg, social media and knowledge bases). An important component of …

Detecting and analyzing dense groups or communities from social and information networks
has attracted immense attention over the last decade due to its enormous applicability in …

Anomaly detection is an important problem with multiple applications, and thus has been
studied for decades in various research domains. In the past decade there has been a …

This chapter characterises the scope of this book. It explains the reasons why one should be
interested in cluster analysis, lists major application areas, basic theoretical and practical …

Classification of various types of tissue in cancer histology images based on the cellular
compositions is an important step towards the development of computational pathology tools …

In today's world, the interconnections among objects in many domains are often modeled as
networks, with nodes representing the objects and edges the existing relationships among …

Community Discovery is among the most studied problems in complex network analysis.
During the last decade, many algorithms have been proposed to address such task; …

The problem of how to coordinate a large fleet of trucks with a given itinerary to enable fuel-
efficient platooning is considered. Platooning is a promising technology that enables trucks …