Community detection is one of the most important tasks in network analysis. It is increasingly
clear that quality measures are not sufficient for assessing communities and structural …

Networks are an adequate representation for modeling and analyzing a great variety of
complex systems. However, understanding networks with millions of nodes and billions of …

In real-world networks, nodes are usually organized into modules or communities of densely
connected nodes. In situations where nodes can belong to multiple communities we say that …

Networks provide an understandable and, in the case of small size, visualizable
representation of data, which allows us to obtain essential information about the …

The gradient descent has proven to be an effective optimization strategy. The current
research proposes a novel clustering methodology using this strategy to recover …

The study of complete sub-graphs belongs to the classical problems of graph theory. Thanks
to sociology, the term clique has come to be used for structures representing a small group …

Large-scale dense networks are very parvasive in various fields such as communication,
social analytics, architecture, bio-metrics, etc. Thus, the need to build a compact version of …

Road networks represented as a networked system of edges and nodes have raised
considerable interest in the literature of networks, leading to numerous studies throughout …

One of the interesting tasks in social network analysis is detecting network nodes' roles in
their interactions. The first problem is discovering such roles, and the second is detecting the …

The analysis of spreading processes within complex networks can offer many important
insights for the application in contexts such as epidemics, information dissemination or …