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Expanding a dictionary of marker words for uncertainty and negation using distributional semantics
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
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2015 (English)In: Empirical Methods in Natural Language Processing, Association for Computational Linguistics , 2015Conference paper, Published paper (Refereed)
Abstract [en]

Approaches to determining the factuality of diagnoses and findings in clinical text tend to rely on dictionaries of marker words for uncertainty and negation. Here, a method for semi-automatically expanding a dictionary of marker words using distributional semantics is presented and evaluated. It is shown that ranking candidates for inclusion according to their proximity to cluster centroids of semantically similar seed words is more successful than ranking them according to proximity to each individual seed word.

Place, publisher, year, edition, pages
Association for Computational Linguistics , 2015.
Keyword [en]
dictionary expansion, distributional semantics
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-122815ISBN: 978-1-941643-32-7 (print)OAI: oai:DiVA.org:su-122815DiVA: diva2:868629
Available from: 2015-11-11 Created: 2015-11-10 Last updated: 2015-11-11

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fulltext(563 kB)54 downloads
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File name FULLTEXT01.pdfFile size 563 kBChecksum SHA-512
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf