Supervision : Patrick GALLINARI

Co-supervision : GUIGUE Vincent

Personnalized access to information : taking the user's dynamic into account

The main goal of this thesis resides in using rich and efficient profiling to improve the adequation between the retrieved information and the user's expectations. We focus on exploiting as much feedback as we can (being clicks, ratings or written reviews) as well as context. In the meantime, the tremendous growth of ubiquitous computing forces us to rethink the role of information access platforms. Therefore, we took interest not solely in performances but also in accompanying users through their access to the information.
Throughout this thesis, we focused on users dynamics modeling. Not only it improves the system performances but it also brings some kind of explicativity to the recommendation. Thus, we propose to accompany the user through his experience accessing information instead of constraining him to a given set of items the systems finds fitting.

2013-2017 Publications

• 2017
  • E. Guardia Sebaoun : “Personnalized access to information : taking the user’s dynamic into account”, thesis, phd defence 11/27/2017, supervision Gallinari, Patrick, co-supervision : Guigue, Vincent (2017)
• 2016
  • E. Guardia‑Sebaoun, V. Guigue, P. Gallinari : “Apprentissage de trajectoires temporelles pour la recommandation dans les communautés d’utilisateurs”, CAp, Marseille, France (2016)
• 2015
  • E. Guardia‑Sebaoun, V. Guigue, P. Gallinari : “Latent Trajectory Modeling: a Light and Efficient Way to Introduce Time in Recommender Systems”, RecSys, Vienne, Austria (2015)
• 2014
  • M. Poussevin, E. Guardia‑Sebaoun, V. Guigue, P. Gallinari : “Recommandation par combinaison de filtrage collaboratif et d’analyse de sentiments”, CORIA 2014 - COnférence en Recherche d’Information et Applications, Nancy, France, pp. 27-42 (2014)
  • E. Guàrdia Sebaoun, V. Guigue, P. Gallinari : “Recommandation Dynamique dans les Graphes Géographiques”, MARAMI 2014 : 5ième conférence sur les modèles et l'analyse des réseaux : Approches mathématiques et informatiques, Paris, France (2014)
• 2013
  • E. Guardia‑Sebaoun, A. Rafrafi, V. Guigue, P. Gallinari : “Cross-Media Sentiment Classification and Application to Box-Office Forecasting”, Proceedings of the 10^th Conference on Open Research Areas in Information Retrieval (OAIR '13), Lisbon, Portugal, pp. 201-208 (2013)