# MeqSum

### Paper

Title: `On the Summarization of Consumer Health Questions`

Abstract: [https://aclanthology.org/P19-1215/](https://aclanthology.org/P19-1215/)

Question understanding is one of the main challenges in question answering. In real world
applications, users often submit natural language questions that are longer than needed
and include peripheral information that increases the complexity of the question, leading
to substantially more false positives in answer retrieval. In this paper, we study neural
abstractive models for medical question summarization. We introduce the MeQSum corpus of
1,000 summarized consumer health questions.


### Citation

```bibtex
@inproceedings{ben-abacha-demner-fushman-2019-summarization,
    title = "On the Summarization of Consumer Health Questions",
    author = "Ben Abacha, Asma  and
      Demner-Fushman, Dina",
    booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/P19-1215",
    doi = "10.18653/v1/P19-1215",
    pages = "2228--2234"}
```
