Abstract
The availability of huge amount of biomedical literature have opened up new possibilities to apply Information Retrieval and NLP for mining documents from them. In this work, we are focusing on biomedical document retrieval from literature for clinical decision support systems. We compare statistical and NLP based approaches of query reformulation for biomedical document retrieval. Also, we have modeled the biomedical document retrieval as a learning to rank problem. We report initial results for statistical and NLP based query reformulation approaches and learning to rank approach with future direction of research.- Anthology ID:
- P18-3012
- Volume:
- Proceedings of ACL 2018, Student Research Workshop
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Editors:
- Vered Shwartz, Jeniya Tabassum, Rob Voigt, Wanxiang Che, Marie-Catherine de Marneffe, Malvina Nissim
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 84–90
- Language:
- URL:
- https://aclanthology.org/P18-3012
- DOI:
- 10.18653/v1/P18-3012
- Cite (ACL):
- Jainisha Sankhavara. 2018. Biomedical Document Retrieval for Clinical Decision Support System. In Proceedings of ACL 2018, Student Research Workshop, pages 84–90, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- Biomedical Document Retrieval for Clinical Decision Support System (Sankhavara, ACL 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/P18-3012.pdf