Abstract
In the biomedical and clinical domain, valuable information is frequently represented in free-text documents. Natural language processing (NLP) is a powerful tool that can extract structured information from theses documents. Word sense disambiguation (WSD) is a critical component in an NLP pipeline that increases the accuracy of the extracted information. However, WSD is expensive to apply for all known ambiguous words. Given limited time and resources, one practical strategy is to prioritize easy-to-disambiguate words and efficiently maximize the coverage of disambiguation. To aid prioritization efforts, we studied two quantitative indicators that are associated with how easy/difficult it is to disambiguate any given word.
Original language | English (US) |
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Title of host publication | Proceedings - 2015 IEEE International Conference on Healthcare Informatics, ICHI 2015 |
Editors | Wai-Tat Fu, Prabhakaran Balakrishnan, Sanda Harabagiu, Fei Wang, Jaideep Srivatsava |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Number of pages | 1 |
ISBN (Electronic) | 9781467395489 |
DOIs | |
State | Published - Dec 8 2015 |
Externally published | Yes |
Event | 3rd IEEE International Conference on Healthcare Informatics, ICHI 2015 - Dallas, United States Duration: Oct 21 2015 → Oct 23 2015 |
Other
Other | 3rd IEEE International Conference on Healthcare Informatics, ICHI 2015 |
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Country/Territory | United States |
City | Dallas |
Period | 10/21/15 → 10/23/15 |
Keywords
- Medical Informatics
- Natural Language Processing
- Word Sense Disambiguation
ASJC Scopus subject areas
- Health Informatics