UZH@SMM4H: System Descriptions
2018-10-01WS 2018Unverified0· sign in to hype
Tilia Ellendorff, Joseph Cornelius, Heath Gordon, Nicola Colic, Fabio Rinaldi
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Our team at the University of Z\"urich 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.