@inproceedings{inglis-etal-2017-textually,
    title = "Textually Summarising Incomplete Data",
    author = "Inglis, Stephanie  and
      Reiter, Ehud  and
      Sripada, Somayajulu",
    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/W17-3535/",
    doi = "10.18653/v1/W17-3535",
    pages = "228--232",
    abstract = "Many data-to-text NLG systems work with data sets which are incomplete, ie some of the data is missing. We have worked with data journalists to understand how they describe incomplete data, and are building NLG algorithms based on these insights. A pilot evaluation showed mixed results, and highlighted several areas where we need to improve our system."
}