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Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes
This paper describes the Duluth systems that participated in the Sentiment Analysis track of the i2b2/VA/Cincinnati Children’s 2011 Challenge. The top Duluth system was a rule-based approach derived through manual corpus analysis and the use of measures of association to identify significant ngrams....
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Libertas Academica
2012
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3409475/ https://www.ncbi.nlm.nih.gov/pubmed/22879775 http://dx.doi.org/10.4137/BII.S8953 |
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author | Pedersen, Ted |
author_facet | Pedersen, Ted |
author_sort | Pedersen, Ted |
collection | PubMed |
description | This paper describes the Duluth systems that participated in the Sentiment Analysis track of the i2b2/VA/Cincinnati Children’s 2011 Challenge. The top Duluth system was a rule-based approach derived through manual corpus analysis and the use of measures of association to identify significant ngrams. This performed in the median range of systems, attaining an F-measure of 0.45. The second system was automatically derived from the most frequent bigrams unique to one or two emotions. It achieved an F-measure of 0.36. The third system was the union of the first two, and reached an F-measure of 0.44. |
format | Online Article Text |
id | pubmed-3409475 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Libertas Academica |
record_format | MEDLINE/PubMed |
spelling | pubmed-34094752012-08-09 Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes Pedersen, Ted Biomed Inform Insights Original Research This paper describes the Duluth systems that participated in the Sentiment Analysis track of the i2b2/VA/Cincinnati Children’s 2011 Challenge. The top Duluth system was a rule-based approach derived through manual corpus analysis and the use of measures of association to identify significant ngrams. This performed in the median range of systems, attaining an F-measure of 0.45. The second system was automatically derived from the most frequent bigrams unique to one or two emotions. It achieved an F-measure of 0.36. The third system was the union of the first two, and reached an F-measure of 0.44. Libertas Academica 2012-01-30 /pmc/articles/PMC3409475/ /pubmed/22879775 http://dx.doi.org/10.4137/BII.S8953 Text en © the author(s), publisher and licensee Libertas Academica Ltd. This is an open access article. Unrestricted non-commercial use is permitted provided the original work is properly cited. |
spellingShingle | Original Research Pedersen, Ted Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes |
title | Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes |
title_full | Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes |
title_fullStr | Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes |
title_full_unstemmed | Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes |
title_short | Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes |
title_sort | rule-based and lightly supervised methods to predict emotions in suicide notes |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3409475/ https://www.ncbi.nlm.nih.gov/pubmed/22879775 http://dx.doi.org/10.4137/BII.S8953 |
work_keys_str_mv | AT pedersented rulebasedandlightlysupervisedmethodstopredictemotionsinsuicidenotes |