Classification Betters Regression in Query-based Multi-document Summarisation Techniques for Question Answering: Macquarie University at BioASQ7b
Computation and Language
2020-08-28 v1
Abstract
Task B Phase B of the 2019 BioASQ challenge focuses on biomedical question answering. Macquarie University's participation applies query-based multi-document extractive summarisation techniques to generate a multi-sentence answer given the question and the set of relevant snippets. In past participation we explored the use of regression approaches using deep learning architectures and a simple policy gradient architecture. For the 2019 challenge we experiment with the use of classification approaches with and without reinforcement learning. In addition, we conduct a correlation analysis between various ROUGE metrics and the BioASQ human evaluation scores.
Cite
@article{arxiv.1909.00542,
title = {Classification Betters Regression in Query-based Multi-document Summarisation Techniques for Question Answering: Macquarie University at BioASQ7b},
author = {Diego Molla and Christopher Jones},
journal= {arXiv preprint arXiv:1909.00542},
year = {2020}
}
Comments
12 pages, 3 figures, 7 tables. As accepted at BioASQ workshop, ECML-PKDD 2019