TY - GEN
T1 - Keyphrases Extraction from User-Generated Contents in Healthcare Domain Using Long Short-Term Memory Networks
AU - Saputra, Ilham Fathy
AU - Mahendra, Rahmad
AU - Wicaksono, Alfan Farizki
N1 - Publisher Copyright:
©2018 Association for Computational Linguistics
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85080909790&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85080909790
T3 - BioNLP 2018 - SIGBioMed Workshop on Biomedical Natural Language Processing, Proceedings of the 17th BioNLP Workshop
SP - 28
EP - 34
BT - BioNLP 2018 - SIGBioMed Workshop on Biomedical Natural Language Processing, Proceedings of the 17th BioNLP Workshop
PB - Association for Computational Linguistics (ACL)
T2 - 17th SIGBioMed Workshop on Biomedical Natural Language Processing, BioNLP 2018
Y2 - 19 July 2018
ER -