Évolution Des Profils D'entités À L'aide D'un Modèle De Langue Sensible Au Temps

Finding important information in real time on a particular named entity is a real challenge. It requires to be able to detect the entity within the document and to be able to assess how important the information is regarding the entity. In this article, we formalize a new time-aware langue model that we use as part of entity profiles. We design meta criteria to fully use this new profile design. Using meta criteria ensure to have a entity independent system and make our approach semi supervised. We evaluate our approach on the data from the TREC on the KBA 2013 track and we obtain satisfying results and interesting conclusions. MOTS-CLES : entites nommees, modele de langue sensible au temps, filtrage de documents, classification, meta criteres.