28 citations · 40 across the 13 of their papers we have counts for
15 papers
BBK: a simpler, faster algorithm for enumerating maximal bicliques in large sparse bipartite graphs
Alexis Baudin, Clémence Magnien, Lionel Tabourier
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 c…
LSCPM: communities in massive real-world Link Streams by Clique Percolation Method
Alexis Baudin, Lionel Tabourier, Clémence Magnien
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 t…
Faster maximal clique enumeration in large real-world link streams
Alexis Baudin, Clémence Magnien, Lionel Tabourier
Link streams offer a good model for representing interactions over time. They consist of links , where and are vertices interacting during the whole time interva…
Compressing bipartite graphs with a dual reordering scheme
Maximilien Danisch, Ioannis Panagiotas, Lionel Tabourier
In order to manage massive graphs in practice, it is often necessary to resort to graph compression, which aims at reducing the memory used when storing and processing the graph. E…
Tailored vertex ordering for faster triangle listing in large graphs
Fabrice Lécuyer, Louis Jachiet, Clémence Magnien +1
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 hig…
Testing the Impact of Semantics and Structure on Recommendation Accuracy and Diversity
Pedro Ramaciotti Morales, Lionel Tabourier, Raphaël Fournier-S'niehotta
The Heterogeneous Information Network (HIN) formalism is very flexible and enables complex recommendations models. We evaluate the effect of different parts of a HIN on the accurac…
Measuring Diversity in Heterogeneous Information Networks
Pedro Ramaciotti Morales, Robin Lamarche-Perrin, Raphael Fournier-S'niehotta +3
Diversity is a concept relevant to numerous domains of research varying from ecology, to information theory, and to economics, to cite a few. It is a notion that is steadily gainin…
Predicting interactions between individuals with structural and dynamical information
Thibaud Arnoux, Lionel Tabourier, Matthieu Latapy
Capturing both the structural and temporal aspects of interactions is crucial for many real world datasets like contact between individuals. Using the link stream formalism to capt…
Predicting links in ego-networks using temporal information
Lionel Tabourier, Anne-Sophie Libert, Renaud Lambiotte
Link prediction appears as a central problem of network science, as it calls for unfolding the mechanisms that govern the micro-dynamics of the network. In this work, we are intere…
RankMerging: A supervised learning-to-rank framework to predict links in large social network
Lionel Tabourier, Daniel Faria Bernardes, Anne-Sophie Libert +1
Uncovering unknown or missing links in social networks is a difficult task because of their sparsity and because links may represent different types of relationships, characterized…
A data-driven analysis to question epidemic models for citation cascades on the blogosphere
Abdelhamid Salah Brahim, Lionel Tabourier, Bénédicte Le Grand
Citation cascades in blog networks are often considered as traces of information spreading on this social medium. In this work, we question this point of view using both a structur…
Directedness of information flow in mobile phone communication networks
Fernando Peruani, Lionel Tabourier
Without having direct access to the information that is being exchanged, traces of information flow can be obtained by looking at temporal sequences of user interactions. These seq…
Intrinsically Dynamic Network Communities
Bivas Mitra, Lionel Tabourier, Camille Roth
Community finding algorithms for networks have recently been extended to dynamic data. Most of these recent methods aim at exhibiting community partitions from successive graph sna…
Internal links and pairs as a new tool for the analysis of bipartite complex networks
Oussama Allali, Lionel Tabourier, Clémence Magnien +1
Many real-world complex networks are best modeled as bipartite (or 2-mode) graphs, where nodes are divided into two sets with links connecting one side to the other. However, there…
Generating constrained random graphs using multiple edge switches
Lionel Tabourier, Camille Roth, Jean-Philippe Cointet
The generation of random graphs using edge swaps provides a reliable method to draw uniformly random samples of sets of graphs respecting some simple constraints, e.g. degree distr…