@InProceedings{aissa-soulier-denoyer:2018:SCAI,
  author    = {Aissa, Wafa  and  Soulier, Laure  and  Denoyer, Ludovic},
  title     = {A Reinforcement Learning-driven Translation Model for Search-Oriented Conversational Systems},
  booktitle = {Proceedings of the 2018 EMNLP Workshop SCAI: The 2nd International Workshop on Search-Oriented Conversational AI},
  month     = {October},
  year      = {2018},
  address   = {Brussels, Belgium},
  publisher = {Association for Computational Linguistics},
  pages     = {33--39},
  abstract  = {Search-oriented conversational systems rely on information needs expressed in natural language (NL). We focus here on the understanding of NL expressions for building keyword-based queries. We propose a reinforcement-learning-driven translation model framework able to 1) learn the translation from NL expressions to queries in a supervised way, and, 2) to overcome the lack of large-scale dataset by framing the translation model as a word selection approach and injecting relevance feedback as a reward in the learning process. Experiments are carried out on two TREC datasets. We outline the effectiveness of our approach in a retrieval task.},
  url       = {http://www.aclweb.org/anthology/W18-5705}
}