Finding Difficult-to-Disambiguate Words: Towards an Efficient Workflow to Implement Word Sense Disambiguation

Manabu Torii, Jung Wei Fan, Daniel S. Zisook

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE International Conference on Healthcare Informatics, ICHI 2015
EditorsWai-Tat Fu, Prabhakaran Balakrishnan, Sanda Harabagiu, Fei Wang, Jaideep Srivatsava
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages448
Number of pages1
ISBN (Electronic)9781467395489
DOIs
StatePublished - Dec 8 2015
Event3rd IEEE International Conference on Healthcare Informatics, ICHI 2015 - Dallas, United States
Duration: Oct 21 2015Oct 23 2015

Publication series

NameProceedings - 2015 IEEE International Conference on Healthcare Informatics, ICHI 2015

Other

Other3rd IEEE International Conference on Healthcare Informatics, ICHI 2015
Country/TerritoryUnited States
CityDallas
Period10/21/1510/23/15

Keywords

  • Medical Informatics
  • Natural Language Processing
  • Word Sense Disambiguation

ASJC Scopus subject areas

  • Health Informatics

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