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MARAMI 2020: Virtual Event
- Roberto Interdonato:
Proceedings of MARAMI 2020 - Modèles & Analyse des Réseaux : Approches Mathématiques & Informatiques - The 11th Conference on Network Modeling and Analysis, Virtual Conference, October 14-15, 2020. CEUR Workshop Proceedings 2750, CEUR-WS.org 2020
Session 1: Network models and measures
- Zakariya Ghalmane, Chantal Cherifi, Hocine Cherifi, Mohammed El Hassouni:
A backbone extraction method for complex weighted networks (extended abstract). - Sarra Djemili, Claudia Marinica, Maria Malek, Dimitris Kotzinos:
Un nouveau modèle pour l'évolution de réseaux sociaux personnels (A new evolution model for personal social networks) (extended abstract). - Stephany Rajeh, Marinette Savonnet, Éric Leclercq, Hocine Cherifi:
An Empirical Comparison of Centrality and Hierarchy Measures in Complex Networks (extended abstract).
Session 2: Communities
- Nejat Arinik, Rosa Figueiredo, Vincent Labatut:
Characterizing measures for the assessment of cluster analysis and community detection (extended abstract). - Rémy Cazabet, Giulio Rossetti, Letizia Milli:
CDlib: a Python Library to Extract, Compare and Evaluate Communities from Complex Networks (extended abstract). - Soroosh Shalileh, Boris G. Mirkin:
Detection of an Unspecified Number of Communities in Feature-Rich Networks. - Raphaël Charbey, Cécile Bothorel, Laurent Brisson:
Énumération de motifs dans un graphe d'évolution de communautés (Pattern mining in community evolution graph).
Session 3: Applied Network Science
- Noé Cecillon, Richard Dufour, Vincent Labatut, Georges Linarès:
Tuning Graph2vec with Node Labels for Abuse Detection in Online Conversations (extended abstract). - Fabio Mensi, Angelo Furno, Rémy Cazabet:
Traffic speed prediction in the Lyon area using DCRNN (extended abstract). - Claire Prudhomme, Christophe Cruz, Hocine Cherifi:
An Agent based model for the transmission and control of the COVID-19 in Dijon (extended abstract). - Jérémy Bourgoin, Quentin Grislain, Roberto Interdonato, Matteo Zignani, Sabrina Gaito:
Mining the miners: acknowledging the magnitude of mining deals through data science (extended abstract).
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