activity
20132016
most citedA Method for Characterizing Communities in Dynamic Attributed Complex Networks

12 citations · 23 across the 5 of their papers we have counts for

collaborators

5 papers

cs.DS2016

Anytime Discovery of a Diverse Set of Patterns with Monte Carlo Tree Search

Guillaume Bosc, Jean-François Boulicaut, Chedy Raïssi +1

The discovery of patterns that accurately discriminate one class label from another remains a challenging data mining task. Subgroup discovery (SD) is one of the frameworks that en…

cs.AI2015

Identifying Avatar Aliases in Starcraft 2

Olivier Cavadenti, Victor Codocedo, Jean-François Boulicaut +1

In electronic sports, cyberathletes conceal their online training using different avatars (virtual identities), allowing them not being recognized by the opponents they may face in…

cs.SI2015★ 11 cited

Interpreting communities based on the evolution of a dynamic attributed network

Günce Orman, Vincent Labatut, Marc Plantevit +1

Many methods have been proposed to detect communities, not only in plain, but also in attributed, directed or even dynamic complex networks. From the modeling point of view, to be…

cs.SI2014★ 12 cited

A Method for Characterizing Communities in Dynamic Attributed Complex Networks

Günce Keziban Orman, Vincent Labatut, Marc Plantevit +1

Many methods have been proposed to detect communities, not only in plain, but also in attributed, directed or even dynamic complex networks. In its simplest form, a community struc…

cs.SI2013

Une méthode pour caractériser les communautés des réseaux dynamiques à attributs

Günce Keziban Orman, Vincent Labatut, Marc Plantevit +1

Many complex systems are modeled through complex networks whose analysis reveals typical topological properties. Amongst those, the community structure is one of the most studied.…