Singh, G;
Thomas, J;
Marshall, IJ;
Shawe-Taylor, J;
Wallace, BC;
(2018)
Structured Multi-Label Biomedical Text Tagging via Attentive Neural Tree Decoding.
In: Riloff, E and Chiang, D and Hockenmaier, J and Tsujii, J, (eds.)
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing.
(pp. pp. 2837-2842).
Association for Computational Linguistics: Brussels, Belgium.
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Abstract
We propose a model for tagging unstructured texts with an arbitrary number of terms drawn from a tree-structured vocabulary (i.e., an ontology). We treat this as a special case of sequence-to-sequence learning in which the decoder begins at the root node of an ontological tree and recursively elects to expand child nodes as a function of the input text, the current node, and the latent decoder state. We demonstrate that this method yields state-of-the-art results on the important task of assigning MeSH terms to biomedical abstracts.
| Type: | Proceedings paper |
|---|---|
| Title: | Structured Multi-Label Biomedical Text Tagging via Attentive Neural Tree Decoding |
| Event: | 2018 Conference on Empirical Methods in Natural Language Processing |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.18653/v1/D18-1308 |
| Publisher version: | http://dx.doi.org/10.18653/v1/D18-1308 |
| Language: | English |
| Additional information: | This is an Open Access paper published under a Creative Commons Attribution 4.0 International (CC BY 4.0) licence (https://creativecommons.org/licenses/by/4.0/). |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Social Research Institute UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10094342 |
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