Classification Betters Regression in Query-based Multi-document Summarisation Techniques for Question Answering: Macquarie University at BioASQ7b
September 02, 2019 ยท Declared Dead ยท ๐ Machine Learning and Knowledge Discovery in Databases
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Authors
Diego Molla, Christopher Jones
arXiv ID
1909.00542
Category
cs.CL: Computation & Language
Citations
10
Venue
Machine Learning and Knowledge Discovery in Databases
Last Checked
4 months ago
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.
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