@inproceedings{ellendorff-etal-2018-uzh,
title = "{UZH}@{SMM}4{H}: System Descriptions",
author = "Ellendorff, Tilia and
Cornelius, Joseph and
Gordon, Heath and
Colic, Nicola and
Rinaldi, Fabio",
editor = "Gonzalez-Hernandez, Graciela and
Weissenbacher, Davy and
Sarker, Abeed and
Paul, Michael",
booktitle = "Proceedings of the 2018 {EMNLP} Workshop {SMM}4{H}: The 3rd Social Media Mining for Health Applications Workshop {\&} Shared Task",
month = oct,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-5916",
doi = "10.18653/v1/W18-5916",
pages = "56--60",
abstract = {Our team at the University of Z{\"u}rich participated in the first 3 of the 4 sub-tasks at the Social Media Mining for Health Applications (SMM4H) shared task. We experimented with different approaches for text classification, namely traditional feature-based classifiers (Logistic Regression and Support Vector Machines), shallow neural networks, RCNNs, and CNNs. This system description paper provides details regarding the different system architectures and the achieved results.},
}
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<abstract>Our team at the University of Zürich participated in the first 3 of the 4 sub-tasks at the Social Media Mining for Health Applications (SMM4H) shared task. We experimented with different approaches for text classification, namely traditional feature-based classifiers (Logistic Regression and Support Vector Machines), shallow neural networks, RCNNs, and CNNs. This system description paper provides details regarding the different system architectures and the achieved results.</abstract>
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%0 Conference Proceedings
%T UZH@SMM4H: System Descriptions
%A Ellendorff, Tilia
%A Cornelius, Joseph
%A Gordon, Heath
%A Colic, Nicola
%A Rinaldi, Fabio
%Y Gonzalez-Hernandez, Graciela
%Y Weissenbacher, Davy
%Y Sarker, Abeed
%Y Paul, Michael
%S Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task
%D 2018
%8 October
%I Association for Computational Linguistics
%C Brussels, Belgium
%F ellendorff-etal-2018-uzh
%X Our team at the University of Zürich participated in the first 3 of the 4 sub-tasks at the Social Media Mining for Health Applications (SMM4H) shared task. We experimented with different approaches for text classification, namely traditional feature-based classifiers (Logistic Regression and Support Vector Machines), shallow neural networks, RCNNs, and CNNs. This system description paper provides details regarding the different system architectures and the achieved results.
%R 10.18653/v1/W18-5916
%U https://aclanthology.org/W18-5916
%U https://doi.org/10.18653/v1/W18-5916
%P 56-60
Markdown (Informal)
[UZH@SMM4H: System Descriptions](https://aclanthology.org/W18-5916) (Ellendorff et al., EMNLP 2018)
ACL
- Tilia Ellendorff, Joseph Cornelius, Heath Gordon, Nicola Colic, and Fabio Rinaldi. 2018. UZH@SMM4H: System Descriptions. In Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task, pages 56–60, Brussels, Belgium. Association for Computational Linguistics.