Quantifying paedophile queries in a large P2P system. - Matthieu Latapy; Clémence Magnien; Raphaël Fournier (INFOCOM, 2011)

Comparing paedophile activity in different P2P systems - Raphaël Fournier; Thibault Cholez; Matthieu Latapy; Clémence Magnien; Isabelle Chrisment; Ivan Daniloff; Olivier Festor (CoRR, 2012)

Détection et analyse d'une thématique rare dans de grands ensembles de requêtes: l'activité pédophile dans le P2P. (Detection and analysis of a rare topic in large sets of search engine queries: paedophile activity in P2P networks). - Raphaël Fournier-S'niehotta (2012)

Quantifying paedophile activity in a large P2P system. - Matthieu Latapy; Clémence Magnien; Raphaël Fournier (Inf. Process. Manag., 2013)

Mining bipartite graphs to improve semantic pedophile activity detection. - Raphaël Fournier; Maximilien Danisch (RCIS, 2014)

A Social Formalism and Survey for Recommender Systems. - Daniel Faria Bernardes; Mamadou Diaby; Raphaël Fournier; Françoise Fogelman-Soulié; Emmanuel Viennet (SIGKDD Explor., 2014)

Analysis of the Temporal and Structural Features of Threads in a Mailing-List. - Noé Gaumont; Tiphaine Viard; Raphaël Fournier-S'niehotta; Qinna Wang; Matthieu Latapy (CompleNet, 2016)

Querying XML Score Databases: XQuery is not Enough!. - Raphaël Fournier-S'niehotta; Philippe Rigaux; Nicolas Travers (ISMIR, 2016)

Querying Music Notation. - Raphaël Fournier-S'niehotta; Philippe Rigaux; Nicolas Travers (TIME, 2016)

Discovering Patterns of Interest in IP Traffic Using Cliques in Bipartite Link Streams. - Tiphaine Viard; Raphaël Fournier-S'niehotta; Clémence Magnien; Matthieu Latapy (CoRR, 2017)

Movie rating prediction using content-based and link stream features. - Tiphaine Viard; Raphaël Fournier-S'niehotta (CoRR, 2018)

Modeling Music as Synchronized Time Series: Application to Music Score Collections. - Raphaël Fournier-S'niehotta; Philippe Rigaux; Nicolas Travers (Inf. Syst., 2018)

A diff procedure for music score files. - Francesco Foscarin; Florent Jacquemard; Raphaël Fournier-S'niehotta (DLfM, 2019)

Augmenting content-based rating prediction with link stream features. - Tiphaine Viard; Raphaël Fournier-S'niehotta (Comput. Networks, 2019)

Testing the Impact of Semantics and Structure on Recommendation Accuracy and Diversity. - Pedro Ramaciotti Morales; Lionel Tabourier; Raphaël Fournier-S'niehotta (ASONAM, 2020)

PKSpell: Data-Driven Pitch Spelling and Key Signature Estimation. - Francesco Foscarin; Nicolas Audebert; Raphaël Fournier-S'niehotta (ISMIR, 2021)

Web Image Context Extraction with Graph Neural Networks and Sentence Embeddings on the DOM Tree. - Chen Dang; Hicham Randrianarivo; Raphaël Fournier-S'niehotta; Nicolas Audebert (PKDD/ECML Workshops (1), 2021)

Measuring diversity in heterogeneous information networks. - Pedro Ramaciotti Morales; Robin Lamarche-Perrin; Raphaël Fournier-S'niehotta; Rémy Poulain; Lionel Tabourier; Fabien Tarissan (Theor. Comput. Sci., 2021)

A Framework for Content-Based Search in Large Music Collections. - Tiange Zhu; Raphaël Fournier-S'niehotta; Philippe Rigaux; Nicolas Travers (Big Data Cogn. Comput., 2022)

Parameterisation of Reasoning on Temporal Markov Logic Networks. - Victor David; Raphaël Fournier-S'niehotta; Nicolas Travers (CoRR, 2022)

Documenting the research process. Opportunities and challenges for Bibliometrics and IR. - Enrico Daga; Marilena Daquino; Raphaël Fournier-S'niehotta; Christophe Guillotel-Nothmann; Andrea Scharnhorst (BIR@ECIR, 2023)

NeoMaPy: A Parametric Framework for Reasoning with MAP Inference on Temporal Markov Logic Networks. - Victor David; Raphaël Fournier-S'niehotta; Nicolas Travers (CIKM, 2023)

NeoMaPy: A Framework for Computing MAP Inference on Temporal Knowledge Graphs. - Victor David; Raphaël Fournier-S'niehotta; Nicolas Travers (IJCAI, 2023)

FACETS: A Tool for Improved Exploration of Large Symbolic Music Collections. - Tiange Zhu; Raphaël Fournier-S'niehotta; Philippe Rigaux (DLfM, 2024)

Supra-Laplacian Encoding for Transformer on Dynamic Graphs. - Yannis Karmim; Marc Lafon; Raphaël Fournier-S'niehotta; Nicolas Thome (NeurIPS, 2024)

Temporal receptive field in dynamic graph learning: A comprehensive analysis. - Yannis Karmim; Leshanshui Yang; Raphaël Fournier-S'niehotta; Clément Chatelain 001; Sébastien Adam; Nicolas Thome (CoRR, 2024)

ITEM: Improving Training and Evaluation of Message-Passing based GNNs for top-k recommendation. - Yannis Karmim; Elias Ramzi; Raphaël Fournier-S'niehotta; Nicolas Thome (Trans. Mach. Learn. Res., 2024)

ViLU: Learning Vision-Language Uncertainties for Failure Prediction. - Marc Lafon; Yannis Karmim; Julio Silva-Rodríguez; Paul Couairon; Clément Rambour; Raphaël Fournier-S'niehotta; Ismail Ben Ayed; Jose Dolz; Nicolas Thome (CoRR, 2025)