@inproceedings{saputra-etal-2018-keyphrases,
title = "Keyphrases Extraction from User-Generated Contents in Healthcare Domain Using Long Short-Term Memory Networks",
author = "Saputra, Ilham Fathy and
Mahendra, Rahmad and
Wicaksono, Alfan Farizki",
editor = "Demner-Fushman, Dina and
Cohen, Kevin Bretonnel and
Ananiadou, Sophia and
Tsujii, Junichi",
booktitle = "Proceedings of the {B}io{NLP} 2018 workshop",
month = jul,
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-2304/",
doi = "10.18653/v1/W18-2304",
pages = "28--34",
abstract = "We propose keyphrases extraction technique to extract important terms from the healthcare user-generated contents. We employ deep learning architecture, i.e. Long Short-Term Memory, and leverage word embeddings, medical concepts from a knowledge base, and linguistic components as our features. The proposed model achieves 61.37{\%} F-1 score. Experimental results indicate that our proposed approach outperforms the baseline methods, i.e. RAKE and CRF, on the task of extracting keyphrases from Indonesian health forum posts."
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%0 Conference Proceedings
%T Keyphrases Extraction from User-Generated Contents in Healthcare Domain Using Long Short-Term Memory Networks
%A Saputra, Ilham Fathy
%A Mahendra, Rahmad
%A Wicaksono, Alfan Farizki
%Y Demner-Fushman, Dina
%Y Cohen, Kevin Bretonnel
%Y Ananiadou, Sophia
%Y Tsujii, Junichi
%S Proceedings of the BioNLP 2018 workshop
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F saputra-etal-2018-keyphrases
%X We propose keyphrases extraction technique to extract important terms from the healthcare user-generated contents. We employ deep learning architecture, i.e. Long Short-Term Memory, and leverage word embeddings, medical concepts from a knowledge base, and linguistic components as our features. The proposed model achieves 61.37% F-1 score. Experimental results indicate that our proposed approach outperforms the baseline methods, i.e. RAKE and CRF, on the task of extracting keyphrases from Indonesian health forum posts.
%R 10.18653/v1/W18-2304
%U https://aclanthology.org/W18-2304/
%U https://doi.org/10.18653/v1/W18-2304
%P 28-34
Markdown (Informal)
[Keyphrases Extraction from User-Generated Contents in Healthcare Domain Using Long Short-Term Memory Networks](https://aclanthology.org/W18-2304/) (Saputra et al., BioNLP 2018)
ACL