@inproceedings{neves-etal-2019-evaluation,
    title = "Evaluation of Scientific Elements for Text Similarity in Biomedical Publications",
    author = "Neves, Mariana  and
      Butzke, Daniel  and
      Grune, Barbara",
    editor = "Stein, Benno  and
      Wachsmuth, Henning",
    booktitle = "Proceedings of the 6th Workshop on Argument Mining",
    month = aug,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/W19-4515/",
    doi = "10.18653/v1/W19-4515",
    pages = "124--135",
    abstract = "Rhetorical elements from scientific publications provide a more structured view of the document and allow algorithms to focus on particular parts of the text. We surveyed the literature for previously proposed schemes for rhetorical elements and present an overview of its current state of the art. We also searched for available tools using these schemes and applied four tools for our particular task of ranking biomedical abstracts based on text similarity. Comparison of the tools with two strong baselines shows that the predictions provided by the ArguminSci tool can support our use case of mining alternative methods for animal experiments."
}