Team : ComplexNetworks - Complex Networks
Team leader : Lionel Tabourier Campus Pierre et Marie Curie 25-26/304
Complex Networks occur in many contexts : the internet, the Web, social, biological or judicial networks are examples of these objects, which can be modelled as graphs. Our team studies transverse questions about these objects, and in particular their measurement (acquirement of information about these graphs), metrology (induced bias on the structure by the measurement method), analysis (statistical or structural description), modelling (generating synthetic graphs sharing observed properties), as well as algorithmic questions (either new questions arising from the context or the taking into account of the very large size of these graphs).
Our approach consists in going back and forth between fundamental questions and applied problems, transverse fundamental questions arising from the study of applied problems, and the development of methods to answer these questions leading to applied results, as well as a validation for the relevance of the proposed methods.
Graphs, dynamic networks, link streams, graph measurement, graph models, algorithmics, metrology, social networks, Internet topology
- T. Viard, M. Latapy, C. Magnien : “Computing maximal cliques in link streams”, Theoretical Computer Science, vol. 609 (Part 1), pp. 245-252, (Elsevier) [Viard 2016]
- C. Magnien, A. Medem Kuatse, S. Kirgizov, F. Tarissan : “Towards realistic modeling of IP-level routing topology dynamics”, Networking Science, vol. 3 (1-4), pp. 24-33, (ISBN: 2076-0310) [Magnien 2013]
- R. Hollanders, D. Bernardes, B. Mitra, R. Jungers, J.‑Ch. Delvenne, F. Tarissan : “Data-driven traffic and diffusion modeling in peer-to-peer networks: A real case study”, Network Science, vol. 2 (3), pp. 341-366, (ISBN: 2050-1242) [Hollanders 2014]
- L. Tabourier, A.‑S. Libert, R. Lambiotte : “Predicting links in ego-networks using temporal information”, EPJ Data Science, vol. 5 (1), pp. 1-16 [Tabourier 2016]
- N. Gaumont, C. Magnien, M. Latapy : “Finding remarkably dense sequences of contacts in link streams”, Social Network Analysis and Mining, vol. 6 (1), pp. 87, (Springer) [Gaumont 2016b]
Lionel.Tabourier (at) nulllip6.fr