Renard (Relationship Extraction from NARrative Documents) is a software allowing to tackle several NLP tasks on long narrative texts (especially novels) : named entity recognition, coreference and alias resolution, character network extraction… All details are provided in the paper below.
We are offering a funded PhD position at the LIA (computer science lab of Avignon, France), within the CORNET team (Complex systems, Operations Research for NEtworks and Text), in co-supervision with the ERIC lab (Lyon, France). Topic: Gender dynamics in collaboration networks Location: LIA, CS laboratory of Avignon University, France.Advisory Team: Rosa Figueiredo (LIA), Vincent Labatut (LIA) and Cécile Favre (ERIC).Duration: 3 years starting from September/November 2025.Funding: ANR project EVA – EValuating gender policies in academia through the Analysis of scientific collaboration networks. Standard PhD wage according to French regulations.Application deadline: 11th May 2025 The complete description of the position is available here: https://eva.univ-avignon.fr/wp-content/uploads/sites/34/2025/04/offre.pdf Thank you for sharing this offer with anyone who might be interested. Candidates can contact us following the instructions provided in the above document.
Thesis title: Natural Language Processing for the Representation of Narrative Texts through Character Networks Date: 12/09/2024 – 9 AM Place: CERI’s Ada Lovelace amphitheater. Abstract: A character network represents characters as vertices in a graph, and their relationships as edges between them. In the case of literary works, they model a whole narrative using a single mathematical object. Depending on the needs, their edges can represent different types of interactions between characters: co-occurrence, conversation, direct action… Additionally, the temporal changes in the relationships between characters can be modeled with dynamic networks. Thanks to this flexibility, character networks have been used to tackle a number of tasks, such as literary genre classification, story segmentation, recommendation or summarization. Manually extracting these networks is costly, which is why many researchers interested in automating the process. This, in turn, requires solving different Natural Language Processing (NLP) tasks such as Named Entity Recognition (NER), coreference resolution or speaker attribution. In this thesis, we present contributions to this automatic extraction process in the case of novels, as well as to character network applications. Inspired by the 2019 survey of Labatut and Bost that summarizes existing extraction efforts in a generic extraction framework, we propose Renard, a Plus d'infos
Title: Network Centrality Game for Cyber Deception against Network Epidemic Propagation Date: Tuesday, December 3, 2024 – 3 pm Place: thesis room (salle des thèses) at the Hannah Arendt campus. Abstract: The rise in data breaches and service disruptions increasingly threatens internal security, with potentially devastating consequences for individuals and organizations. As a result, users of information and communication technologies must adopt tools that are both effective and efficient in combating the spread of malware. The term “users” encompasses a wide range of actors, including individuals, businesses, governmental and non-governmental organizations, and states, in short anyone who communicates through modern technologies. Among the most pressing threats they face are lateral movement and widespread epidemic propagation through the covert recruitment of unsuspecting users into botnets, the cyber-terrorist armies capable of inflicting significant damage, such as crippling businesses whose services are used by the same users. In these scenarios, as in many others, users, deceived by skilled experts known as attackers, unknowingly contribute to cyberattacks, with deception serving as the primary attack vector. Cybercriminals, unlike defenders, frequently violate privacy rules, allowing them to be better informed, sometimes unilaterally, about the level of compromise of each user. In their efforts to control multiple Plus d'infos
Title: The Capacitated p-Location Problem with Territorial Coverage Constraints Date: 11/07/2024 – 11:35 AM Room: S6 Résumé : In spatial planning, the efficient location and allocation of services pose complex challenges across diverse contexts. Our research focuses on the capacitated p-location problem, which aims to select p facilities from a set of potential locations to minimize allocation costs between facilities and consumers with specific demand weights, while respecting capacity constraints. To better model real-world applications, we extended this problem by introducing territorial coverage constraints. We examined the adapted formulation of this expanded problem and developed a heuristic approach to handle larger instances effectively. A case study in France’s PACA (Provence-Alpes-Côte d’Azur) region illustrates the impact of these coverage constraints.
Le prochain séminaire de l’équipe CORNET se tiendra le 24 septembre à 11h35 en salle C057 (ancienne BU). Nous aurons le plaisir d’accueillir Léo Joubert, Maître de Conférences du laboratoire Dysolab à l’Université de Rouen-Normandie, qui nous présentera : _________________________________________________________ De quoi est faite Wikipédia ? Quelques pistes pour une analyse de sa régulation au prisme des effacements réciproques. Résumé : Vieille de 20 ans et aujourd’hui largement utilisée, l’encyclopédie Wikipédia continue à interroger par la manière dont elle est produite. Une communauté de « wikipédien.nes » volontaires remplace les habituels expert.es mobilisés par les comités de rédaction. Alors qu’au fil du temps, des règles encadrant la rédaction acquéraient leur légitimité, le volume du corpus augmentait en même temps que son hétérogénéité. Ce séminaire vise à catégoriser cette diversité, dans le but de saisir comment Wikipédia parvient à faire cohabiter différents modes de régulation ajustée à la pluralité des contextes. Nous mobiliserons pour cela une base de données compilant l’ensemble des ajouts et effacements sur l’ensemble des pages wikipédiennes. À partir d’une comparaison de plusieurs sous-corpus, l’analyse statistique constituera le point de départ d’une sociologie de la régulation des communs numériques de masse au regard de la pluralité des formes de coécriture. _________________________________________________________
First CORNET seminar, Tuesday 10th september 2024 11:00, room C057. Anna Melnykova from Mathematics Lab of Avignon (LMA). Abstract: Hawkes processes is a versatile probabilistic tool which permits to model a variety of real-world phenomena: earthquakes, stock markets, population dynamics. In this talk we will focus on its use in neuroscience, where they permit to model interactions between different group of neurons (or individual neurons). Furthermore, due to memory property, models based on Hawkes processes naturally embed the refractory (inter-spiking) period for each individual neuron. The focus of this talk is on numerical and statistical challenges associated with Hawkes processes (simulation, parametric and non-parametric inference, causality).
EValuating gender policies in academia through the Analysis of scientific collaboration networks The ANR EVA project is dedicated to addressing gender disparities within the realm of academia and research. Focused on the fields of computer science, political science, economics, and sociology, which align with our consortium’s research areas, EVA conducts an analysis of gender dynamics within the geographical scope of France and the broader European space. This project aims to contribute to the ongoing efforts to promote gender equality in the scientific community by objectively assessing the impact and effectiveness of gender-related policies and best practices on scientific publication activity. To bridge the gap between existing research on gender dynamics in collaboration networks and evolving policy landscapes, EVA adopts an interdisciplinary approach, bringing together researchers from political science and network analysis. This collaborative initiative produces a shared bibliometric dataset and maps gender policies and recommendations implemented by political institutions and the scientific community within the same specific temporal, disciplinary, and geographical context. This establishes a direct link between gender dynamics and policy initiatives. Methodologically, the EVA project introduces methods for anomaly detection and correction within co-authorship networks, enhancing the quality and accuracy of network analysis. It adheres to open science principles by Plus d'infos
saFe learnINg for lArge scaLe socio-Technical sYstem FINALITY in a Nutshell. FINALITY is a MSCA DN forming a novel AI curriculum for engineering researchers exploring safe techniques for socio-technical systems where human decisions for resource allocation are supported by AI. The ESRs engaged in the FINALITY DN will develop new methodological tools focusing on the following expertise areas: constrained and delayed MDP theory and their application to safe Reinforcement Learning, Online Convex Optimization and Federated Learning under constraints. Liste des partenaires : Responsable Scientifique pour le LIA : Francesco De Pellegrini (Equipe CORNET ) Date Début : 2025-03-01 Date Fin : 2028-03-01 En Savoir Plus
MUGS: Multi-layer graph games for network cyberdeception Développer des modèles avancés de théorie des jeux (jeux stochastiques partiellement observables, apprentissage par renforcement et utilisation des propriétés de centralité/connectivité des graphes…) sur les graphes avec application au contrôle de malware/attaque dans un réseau. Liste des partenaires : Responsable Scientifique pour le LIA : Yezekael Hayel (Équipe CORNET) Date Début : 2024-09-01 Date Fin : 2027-09-01 En Savoir Plus
Laboratoire Informatique d'Avignon — Avignon Université