1. Conference Ramaciotti-Morales, P., Tabourier, L., & Fournier, R. (2020). Testing the Impact of Semantics and Structure on Recommendation Accuracy and Diversity. In IEEE/ACM International Conference on Social Networks Analysis and Mining (ASONAM 2020). Status: accepted.


  1. Journal Viard, T., & Fournier, R. (2019). Augmenting content-based rating prediction with link stream features. Computer Networks, 150, 127–133. DOI: https://doi.org/10.1016/j.comnet.2018.12.002.
  2. Conference Viard, T., & Fournier, R. (2019). Encoding temporal and structural information in machine learning models for recommandation. In LEG @ ECML-PKDD 19. Status: accepted.
  3. Conference Foscarin, F., Fournier, R., & Jacquemard, F. (2019). A diff procedure for XML music score files. In 6th International Conference on Digital Libraries for Musicology (DLfM 2019). Status: accepted.
  4. Conference Foscarin, F., Fournier, R., & Jacquemard, F. (2019). Computation and visualization of differences between two XML music score files. In 20th International Society for Music Information Retrieval Conference, ISMIR 2019 (Late-breaking Demo). Status: accepted.


  1. Conference Viard, T., Fournier, R., Magnien, C., & Latapy, M. (2018). Discovering Patterns of Interest in IP Traffic Using Cliques in Bipartite Link Streams. In (CompleNet’18) International Workshop on Complex Networks. DOI: https://doi.org/10.1007/978-3-319-73198-8_20.


  1. Book Delacroix, J., Barthélémy, F., Fournier, R., Gil-Michalon, I., Lambert, A., Plateau, A., … Waymel, E. (2017). Informatique (1e ed.). Paris : Dunod. Retrieved from https://www.dunod.com/sciences-techniques/informatique.
  2. Journal Fournier, R., Rigaux, P., & Travers, N. (2017). Modeling Music as Synchronized Time Series: Application to Music Score Collections. (IS’18) Information Systems, 1–36. DOI: 10.1016/j.is.2017.12.003.


  1. Conference Gaumont, N., Viard, T., Fournier, R., Wang, Q., & Latapy, M. (2016). Analysis of the temporal and structural features of threads in a mailing-list. In Complex Networks VII - Proceedings of the 7th Workshop on Complex Networks CompleNet 2016, Dijon, France, March 23-25, 2016. DOI: https://doi.org/10.1007/978-3-319-30569-1_8.
  2. Conference Fournier, R., Rigaux, P., & Travers, N. (2016). Is There a Data Model in Music Notation? In R. Hoadley, C. Nash, & D. Fober (Eds.), Proceedings of the International Conference on Technologies for Music Notation and Representation – TENOR’16 (pp. 85–91). Anglia Ruskin University : Cambridge, UK. Retrieved from http://tenor2016.tenor-conference.org.
  3. Conference Fournier, R., Rigaux, P., & Travers, N. (2016). Vers un Traitement Algébrique de la Notation Musicale. In (JIM’16) Journées d’Informatique Musicale (Vol. 23, pp. 1–9). Albi, France. Retrieved from http://jim2016.gmea.net/actes.
  4. Conference Fournier, R., Rigaux, P., & Travers, N. (2016). A Digital Score Library Based on MEI. In (MEC’16) Music Encoding Conference (pp. 1–4). Montréal, Canada.
  5. Conference Fournier, R., Rigaux, P., & Travers, N. (2016). Querying Music Notation. In C. E. Dyreson, M. R. Hansen, & L. Hunsberger (Eds.), 23rd International Symposium on Temporal Representation and Reasoning, TIME 2016, Kongens Lyngby, Denmark, October 17-19, 2016 (pp. 51–59). IEEE. DOI: 10.1109/TIME.2016.13.
  6. Conference Fournier, R., Rigaux, P., & Travers, N. (2016). Querying XML Score Databases: XQuery is not Enough! In M. I. Mandel, J. Devaney, D. Turnbull, & G. Tzanetakis (Eds.), Proceedings of the 17th International Society for Music Information Retrieval Conference, ISMIR 2016, New York City, United States, August 7-11, 2016 (pp. 723–729). Retrieved from https://wp.nyu.edu/ismir2016/wp-content/uploads/sites/2294/2016/07/136_Paper.pdf.


  1. Journal Fournier, R., & Latapy, M. (2015). Temporal Patterns of Pedophile Activity in a P2P Network: First Insights about User Profiles from Big Data. International Journal of Internet Science, 10(1), 8–19. Retrieved from http://www.ijis.net/ijis_inpress/ijis_inpress_Fournier_and_Latapy_pre.html.


  1. Journal Fournier, R., Cholez, T., Latapy, M., Chrisment, I., Magnien, C., Daniloff, I., & Festor, O. (2014). Comparing paedophile activity in different P2P systems. Social Sciences, 3(3). DOI: 10.3390/socsci3030314.
  2. Conference Fournier, R., & Viennet, E. (2014). AMMICO : recommandation sociale pour la visite de musée. In Apprentissage Artificiel et Fouille de Données, AAFD 2014, Université Paris 13, Institut Galilée, Villetaneuse, France, 29-30 avril 2014.
  3. Conference Fournier, R., & Danisch, M. (2014). Mining bipartite graphs to improve semantic paedophile activity detection. In IEEE 8th International Conference on Research Challenges in Information Science, RCIS 2014, Marrakech, Morocco, May 28-30, 2014 (pp. 1–4). DOI: 10.1109/RCIS.2014.6861035.
  4. Journal Bernardes, D., Diaby, M., Fournier, R., Fogelman-Soulié, F., & Viennet, E. (2014). A Social Formalism and Survey for Recommender Systems. SIGKDD Explorations, 16(2), 20–37. DOI: 10.1145/2783702.2783705.


  1. Journal Latapy, M., Magnien, C., & Fournier, R. (2013). Quantifying paedophile activity in a large P2P system. Information Processing and Management, 49(1), 248–263. DOI: 10.1016/j.ipm.2012.02.008.


  1. Ph. D. dissertation Fournier, R. (2012). Détection et analyse d’une thématique rare dans de grands ensembles de requêtes : l’activité pédophile dans le P2P (PhD thesis). UPMC.


  1. Conference Latapy, M., Magnien, C., & Fournier, R. (2011). Quantifying paedophile queries in a large P2P system. In INFOCOM 2011. 30th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, 10-15 April 2011, Shanghai, China (pp. 401–405). IEEE. DOI: 10.1109/INFCOM.2011.5935191.