Zobrazeno 1 - 10
of 107
pro vyhledávání: '"Magnien, Clémence"'
Bipartite graphs are a prevalent modeling tool for real-world networks, capturing interactions between vertices of two different types. Within this framework, bicliques emerge as crucial structures when studying dense subgraphs: they are sets of vert
Externí odkaz:
http://arxiv.org/abs/2405.04428
Community detection is a popular approach to understand the organization of interactions in static networks. For that purpose, the Clique Percolation Method (CPM), which involves the percolation of k-cliques, is a well-studied technique that offers s
Externí odkaz:
http://arxiv.org/abs/2308.10801
Betweenness centrality measure assesses the importance of nodes in a graph and has been used in a variety of contexts. Betweenness centrality has also been extended to temporal graphs. Temporal graphs have edges that bear labels according to the time
Externí odkaz:
http://arxiv.org/abs/2304.09791
Publikováno v:
Journal of Graph Algorithms and Applications. 28, 1 (May 2024), 149-178
Link streams offer a good model for representing interactions over time. They consist of links $(b,e,u,v)$, where $u$ and $v$ are vertices interacting during the whole time interval $[b,e]$. In this paper, we deal with the problem of enumerating maxi
Externí odkaz:
http://arxiv.org/abs/2302.00360
Listing triangles is a fundamental graph problem with many applications, and large graphs require fast algorithms. Vertex ordering allows the orientation of edges from lower to higher vertex indices, and state-of-the-art triangle listing algorithms u
Externí odkaz:
http://arxiv.org/abs/2203.04774
Automatic detection of relevant groups of nodes in large real-world graphs, i.e. community detection, has applications in many fields and has received a lot of attention in the last twenty years. The most popular method designed to find overlapping c
Externí odkaz:
http://arxiv.org/abs/2110.01213
Publikováno v:
IEEE/ACM Transactions on Networking 2021
We introduce an original mathematical model to analyse the diffusion of posts within a generic online social platform. The main novelty is that each user is not simply considered as a node on the social graph, but is further equipped with his/her own
Externí odkaz:
http://arxiv.org/abs/2107.01914
Publikováno v:
Journal of Graph Algorithms and Applications 27:3, 2023
Betweeness centrality is one of the most important concepts in graph analysis. It was recently extended to link streams, a graph generalization where links arrive over time. However, its computation raises non-trivial issues, due in particular to the
Externí odkaz:
http://arxiv.org/abs/2102.06543
Stream graphs model highly dynamic networks in which nodes and/or links arrive and/or leave over time. Strongly connected components in stream graphs were defined recently, but no algorithm was provided to compute them. We present here several soluti
Externí odkaz:
http://arxiv.org/abs/2011.08054
Publikováno v:
In: Holme P., Saram\"aki J. (eds) Temporal Network Theory. Computational Social Sciences. Springer, 2019
We recently introduced a formalism for the modeling of temporal networks, that we call stream graphs. It emphasizes the streaming nature of data and allows rigorous definitions of many important concepts generalizing classical graphs. This includes i
Externí odkaz:
http://arxiv.org/abs/1906.04840