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Expanding a dictionary of marker words for uncertainty and negation using distributional semantics

Alfalahi, Alyaa ; Skeppstedt, Maira ; Ahlblom, Rickard ; Baskalayci, Roza ; Henriksson, Aron ; Asker, Lars ; Paradis, Carita LU orcid and Kerren, Andreas (2015) 6th International Workshop on Health Text Mining and Information Analysis, LOUHI 2015, co-located with EMNLP 2015 p.90-96
Abstract

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.

Please use this url to cite or link to this publication:
author
; ; ; ; ; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
clinical text, negation, uncertainty, marker words, distributional semantics
host publication
EMNLP 2015 - 6th International Workshop on Health Text Mining and Information Analysis, LOUHI 2015 : Proceedings of the Workshop - Proceedings of the Workshop
editor
Grouin, Cyril ; Hamon, Thierry ; Névéol, Aurélie and Zweigenbaum, Pierre
pages
7 pages
publisher
The Association for Computational Linguistics
conference name
6th International Workshop on Health Text Mining and Information Analysis, LOUHI 2015, co-located with EMNLP 2015
conference location
Lisbon, Portugal
conference dates
2015-09-17
external identifiers
  • other:urn:nbn:se:lnu:diva-45648
  • other:oai:DiVA.org:lnu-45648
  • scopus:84992040738
ISBN
9781941643327
project
StaViCTA - Advances in the description and explanation of stance in discourse using visual and computational text analytics
language
English
LU publication?
yes
additional info
Funding Information: This work was partly funded through the project StaViCTA by the framework grant “the Digitized Society Past, Present, and Future” with No. 2012-5659 from the Swedish Research Council (Veten-skapsrådet) and partly by the Swedish Foundation for Strategic Research through the project High-Performance Data Mining for Drug Effect Detection (ref. no. IIS11-0053) at Stockholm University, Sweden. The authors would also like to direct thanks to the reviewers for valuable comments. Publisher Copyright: © 2015 Association for Computational Linguistics.
id
ca58d1c4-4bfa-4f8a-9c4f-9e8291f1ce59 (old id 7763505)
date added to LUP
2016-04-04 13:03:35
date last changed
2022-04-22 20:31:08
@inproceedings{ca58d1c4-4bfa-4f8a-9c4f-9e8291f1ce59,
  abstract     = {{<p>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.</p>}},
  author       = {{Alfalahi, Alyaa and Skeppstedt, Maira and Ahlblom, Rickard and Baskalayci, Roza and Henriksson, Aron and Asker, Lars and Paradis, Carita and Kerren, Andreas}},
  booktitle    = {{EMNLP 2015 - 6th International Workshop on Health Text Mining and Information Analysis, LOUHI 2015 : Proceedings of the Workshop}},
  editor       = {{Grouin, Cyril and Hamon, Thierry and Névéol, Aurélie and Zweigenbaum, Pierre}},
  isbn         = {{9781941643327}},
  keywords     = {{clinical text; negation; uncertainty; marker words; distributional semantics}},
  language     = {{eng}},
  pages        = {{90--96}},
  publisher    = {{The Association for Computational Linguistics}},
  title        = {{Expanding a dictionary of marker words for uncertainty and negation using distributional semantics}},
  url          = {{https://lup.lub.lu.se/search/files/6044942/7869308.pdf}},
  year         = {{2015}},
}