Abstract
Macquarie University’s contribution to the BioASQ challenge (Task 5b Phase B) focused on the use of query-based extractive summarisation techniques for the generation of the ideal answers. Four runs were submitted, with approaches ranging from a trivial system that selected the first n snippets, to the use of deep learning approaches under a regression framework. Our experiments and the ROUGE results of the five test batches of BioASQ indicate surprisingly good results for the trivial approach. Overall, most of our runs on the first three test batches achieved the best ROUGE-SU4 results in the challenge.
Original language | English |
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Title of host publication | BioNLP 2017 |
Subtitle of host publication | SIGBioMed Workshop on Biomedical Natural Language Processing |
Publisher | Association for Computational Linguistics |
Pages | 67-75 |
Number of pages | 9 |
ISBN (Electronic) | 9781945626593 |
DOIs | |
Publication status | Published - 2017 |
Event | 16th SIGBioMed Workshop on Biomedical Natural Language Processing - Vancouver, Canada Duration: 4 Aug 2017 → 4 Aug 2017 |
Conference
Conference | 16th SIGBioMed Workshop on Biomedical Natural Language Processing |
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Country | Canada |
City | Vancouver |
Period | 4/08/17 → 4/08/17 |