Soutenance de thèse Meghdad Farahmand

MF_400.jpg M. Meghdad Farahmand soutiendra, en vue de l'obtention du grade de docteur ès sciences, mention informatique, sa thèse intitulée:

Computational Models of Learning the Idiosyncrasy of Multiword Expressions

 

 

Le jury de thèse est composé de:

  • Prof. Stéphane MARCHAND-MAILLET, Directeur de thèse, Faculté des sciences, Université de Genève
  • Prof. Gilles FALQUET, co-directeur de thèse, GSEM, Université de Genève
  • Prof. Paola MERLO, Faculté des lettres, Université de Genève
  • Dr. Andrei POPESCU-BELIS, Idiap Research Institute/EPFL

Résumé:

Idiomatic or multiword expressions (MWEs) are sequences of words (sometimes with a gap) that can be semantically, syntactically, or statistically idiomatic (idiosyncratic). Examples of  MWEs are flea market and kangaroo court with semantic idiosyncrasy, at large and in short with syntactic idiosyncrasy and drug dealer and finish line with statistical idiosyncrasy. MWEs constitute an interesting topic in natural language processing (NLP) because while idiosyncrasy cannot be readily defined, it still excessively comes up in any language data, whether it is written or spoken and poses major challenges to many NLP applications. Researchers believe that MWEs account for a significant fraction of daily interactions. According to some researchers, MWEs are as many as single words in a speaker's lexicon, but, others believe that even this is an underestimate. In my work, I discuss idiosyncrasy from a computational perspective. I study idiosyncrasy from a statistical and probabilistic viewpoint and explore and adapt different machine learning algorithms for learning this phenomenon.

Date: Vendredi 17 mars 2017 à 16h00

Lieu: Battelle bâtiment A - Salle de cours 404-407 (3ème étage)

9 mars 2017

À la Une

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