Expanding a dictionary of marker words for uncertainty and negation using distributional semantics
Author
Editor
- Cyril Grouin
- Thierry Hamon
- Aurélie Névéol
- Pierre Zweigenbaum
Summary, in English
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.
Department/s
Publishing year
2015
Language
English
Pages
90-96
Publication/Series
EMNLP 2015 - 6th International Workshop on Health Text Mining and Information Analysis, LOUHI 2015 : Proceedings of the Workshop
Full text
- - 527 kB
Links
Document type
Conference paper
Publisher
The Association for Computational Linguistics
Topic
- Computer and Information Sciences
Keywords
- clinical text
- negation
- uncertainty
- marker words
- distributional semantics
Conference name
6th International Workshop on Health Text Mining and Information Analysis, LOUHI 2015, co-located with EMNLP 2015
Conference date
2015-09-17
Conference place
Lisbon, Portugal
Status
Published
Project
- StaViCTA - Advances in the description and explanation of stance in discourse using visual and computational text analytics
ISBN/ISSN/Other
- ISBN: 9781941643327
- urn:nbn:se:lnu:diva-45648
- oai:DiVA.org:lnu-45648