A classification for community discovery methods in complex networks
Many real‐world networks are intimately organized according to a community structure.
Much research effort has been devoted to develop methods and algorithms that can …
Much research effort has been devoted to develop methods and algorithms that can …
Multilayer networks
In most natural and engineered systems, a set of entities interact with each other in
complicated patterns that can encompass multiple types of relationships, change in time and …
complicated patterns that can encompass multiple types of relationships, change in time and …
A survey of community detection methods in multilayer networks
X Huang, D Chen, T Ren, D Wang - Data Mining and Knowledge …, 2021 - Springer
Community detection is one of the most popular researches in a variety of complex systems,
ranging from biology to sociology. In recent years, there's an increasing focus on the rapid …
ranging from biology to sociology. In recent years, there's an increasing focus on the rapid …
[KÖNYV][B] Introduction to graph neural networks
Graphs are useful data structures in complex real-life applications such as modeling
physical systems, learning molecular fingerprints, controlling traffic networks, and …
physical systems, learning molecular fingerprints, controlling traffic networks, and …
[KÖNYV][B] Multilayer social networks
Multilayer networks, in particular multilayer social networks, where users belong to and
interact on different networks at the same time, are an active research area in social network …
interact on different networks at the same time, are an active research area in social network …
ABACUS: frequent pAttern mining-BAsed Community discovery in mUltidimensional networkS
Community discovery in complex networks is the problem of detecting, for each node of the
network, its membership to one of more groups of nodes, the communities, that are densely …
network, its membership to one of more groups of nodes, the communities, that are densely …
Do more views of a graph help? community detection and clustering in multi-graphs
Given a co-authorship collaboration network, how well can we cluster the participating
authors into communities? If we also consider their citation network, based on the same …
authors into communities? If we also consider their citation network, based on the same …
The atlas for the aspiring network scientist
M Coscia - arxiv preprint arxiv:2101.00863, 2021 - arxiv.org
Network science is the field dedicated to the investigation and analysis of complex systems
via their representations as networks. We normally model such networks as graphs: sets of …
via their representations as networks. We normally model such networks as graphs: sets of …
Community detection in multiplex networks using locally adaptive random walks
Multiplex networks, a special type of multilayer networks, are increasingly applied in many
domains ranging from social media analytics to biology. A common task in these …
domains ranging from social media analytics to biology. A common task in these …
Core decomposition and densest subgraph in multilayer networks
Multilayer networks are a powerful paradigm to model complex systems, where various
relations might occur among the same set of entities. Despite the keen interest in a variety of …
relations might occur among the same set of entities. Despite the keen interest in a variety of …