Classification Betters Regression in Query-based Multi-document Summarisation Techniques for Question Answering: Macquarie University at BioASQ7b

September 02, 2019 ยท Declared Dead ยท ๐Ÿ› 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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