UZH@SMM4H: System Descriptions.

Tilia Ellendorff, Joseph Cornelius, Heath Gordon,Nicola Colic,Fabio Rinaldi

SMM4H@EMNLP(2018)

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摘要
Our team at the University of Zurich 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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