"In this master thesis we present a novel approach to finding communities in large graphs. Our method finds the overlapped and hierarchical structure of communities efficiently, outperforming previous proposals. We propose a new objective function that allows to evaluate the quality of a community naturally including nodes shared by other communities. This is achieved by implicitly mapping the nodes of the graph in a vectorial space, using as a basis a construction presented by Lóvasz in 1979. We present and analyse several algorithms to decompose a given graph into a set of not necessarily disjoint neighborhoods. This has applications for analysing and summarizing the large-scale structure of complex networks.
Community structure is observed in many real-world networks in fields ranging from social networking...
Large graphs arise in a number of contexts and understand-ing their structure and extracting informa...
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. With the rapid development of informa...
"In this master thesis we present a novel approach to finding communities in large graphs. Our metho...
Vertices in complex networks can be grouped into communities, where vertices inside communities...
Abstract — Finding decompositions of a graph into a family of clusters is crucial to understanding i...
International audienceDiscovering the latent community structure is cru- cial to understanding the f...
International audienceDiscovering the latent community structure is crucial to understanding the fea...
International audienceCommunity detection, also known as graph clustering, has been extensively stud...
International audienceDetecting and analyzing dense subgroups or communities from social and informa...
International audienceDiscovering the hidden community structure is a fundamental problem in network...
Network communities represent basic structures for understanding the organization of real-world netw...
Finding groups of connected individuals in large graphs with tens of thousands or more nodes has rec...
anonymous submission We present a new approach to the problem of finding communities: a community is...
International audienceIn this paper, we propose a new approach to detect overlapping communities in ...
Community structure is observed in many real-world networks in fields ranging from social networking...
Large graphs arise in a number of contexts and understand-ing their structure and extracting informa...
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. With the rapid development of informa...
"In this master thesis we present a novel approach to finding communities in large graphs. Our metho...
Vertices in complex networks can be grouped into communities, where vertices inside communities...
Abstract — Finding decompositions of a graph into a family of clusters is crucial to understanding i...
International audienceDiscovering the latent community structure is cru- cial to understanding the f...
International audienceDiscovering the latent community structure is crucial to understanding the fea...
International audienceCommunity detection, also known as graph clustering, has been extensively stud...
International audienceDetecting and analyzing dense subgroups or communities from social and informa...
International audienceDiscovering the hidden community structure is a fundamental problem in network...
Network communities represent basic structures for understanding the organization of real-world netw...
Finding groups of connected individuals in large graphs with tens of thousands or more nodes has rec...
anonymous submission We present a new approach to the problem of finding communities: a community is...
International audienceIn this paper, we propose a new approach to detect overlapping communities in ...
Community structure is observed in many real-world networks in fields ranging from social networking...
Large graphs arise in a number of contexts and understand-ing their structure and extracting informa...
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. With the rapid development of informa...