The first step in discourse analysis involves dividing a text into segments. We annotate the first high-quality small-scale medical corpus in English with discourse segments and analyze how well news-trained segmenters perform on this domain. While we expectedly find a drop in performance, the nature of the segmentation errors suggests some problems can be addressed earlier in the pipeline, while others would require expanding the corpus to a trainable size to learn the nuances of the medical domain.
@article{arxiv.1904.06682,
title = {From News to Medical: Cross-domain Discourse Segmentation},
author = {Elisa Ferracane and Titan Page and Junyi Jessy Li and Katrin Erk},
journal= {arXiv preprint arXiv:1904.06682},
year = {2019}
}