@inproceedings{castro-ferreira-paraboni-2017-improving,
    title = "Improving the generation of personalised descriptions",
    author = "Castro Ferreira, Thiago  and
      Paraboni, Ivandr{\'e}",
    editor = "Alonso, Jose M.  and
      Bugar{\'i}n, Alberto  and
      Reiter, Ehud",
    booktitle = "Proceedings of the 10th International Conference on Natural Language Generation",
    month = sep,
    year = "2017",
    address = "Santiago de Compostela, Spain",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest_wac_2008/W17-3536/",
    doi = "10.18653/v1/W17-3536",
    pages = "233--237",
    abstract = "Referring expression generation (REG) models that use speaker-dependent information require a considerable amount of training data produced by every individual speaker, or may otherwise perform poorly. In this work we propose a simple personalised method for this task, in which speakers are grouped into profiles according to their referential behaviour. Intrinsic evaluation shows that the use of speaker`s profiles generally outperforms the personalised method found in previous work."
}