TY - GEN
T1 - Decomposing Consumer Health Questions
AU - Roberts, Kirk
AU - Kilicoglu, Halil
AU - Fiszman, Marcelo
AU - Demner-Fushman, Dina
N1 - Funding Information:
This work was supported by the intramural research program at the U.S. National Library of Medicine, National Institutes of Health. We would additionally like to thank Stephanie M. Morrison and Janine Lewis for their help accessing the GARD data.
Publisher Copyright:
©2014 Association for Computational Linguistics
PY - 2014
Y1 - 2014
N2 - This paper presents a method for decomposing long, complex consumer health questions. Our approach largely decomposes questions using their syntactic structure, recognizing independent questions embedded in clauses, as well as coordinations and exemplifying phrases. Additionally, we identify elements specific to disease-related consumer health questions, such as the focus disease and background information. To achieve this, our approach combines rank-and-filter machine learning methods with rule-based methods. Our results demonstrate significant improvements over the heuristic methods typically employed for question decomposition that rely only on the syntactic parse tree.
AB - This paper presents a method for decomposing long, complex consumer health questions. Our approach largely decomposes questions using their syntactic structure, recognizing independent questions embedded in clauses, as well as coordinations and exemplifying phrases. Additionally, we identify elements specific to disease-related consumer health questions, such as the focus disease and background information. To achieve this, our approach combines rank-and-filter machine learning methods with rule-based methods. Our results demonstrate significant improvements over the heuristic methods typically employed for question decomposition that rely only on the syntactic parse tree.
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M3 - Conference contribution
AN - SCOPUS:85122512931
T3 - Proceedings of the Annual Meeting of the Association for Computational Linguistics
SP - 29
EP - 37
BT - ACL 2014 - BioNLP 2014, Workshop on Biomedical Natural Language Processing, Proceedings of the Workshop
PB - Association for Computational Linguistics (ACL)
T2 - ACL 2014 Workshop on Biomedical Natural Language Processing, BioNLP 2014
Y2 - 27 June 2014 through 28 June 2014
ER -