Pre-trained model with numerical encoding and extension vocabulary for question answering in biomedical domain
- Title
- Pre-trained model with numerical encoding and extension vocabulary for question answering in biomedical domain
- Authors
- 곽재하
- Date Issued
- 2022
- Publisher
- 포항공과대학교
- Abstract
- Extracting and translating information from vast amounts of biomedical literature takes considerable time and energy. In particular, biomedical literature includes various types of terminology and numerical facts, which makes it difficult for humans to interpret. Accordingly, we propose a deep learning-based QA model in which numerical encoding and extension vocabulary are added to solve these problems. The proposed QA model shows excellent performance even with further pre-training using a small amount of biomedical dataset.
- URI
- http://postech.dcollection.net/common/orgView/200000635222
https://oasis.postech.ac.kr/handle/2014.oak/117347
- Article Type
- Thesis
- Files in This Item:
- There are no files associated with this item.
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