Fusion of Neural Features and Predicted Class Probabilities for Suicide Risk Assessment Based on Online Posts

Hessam Amini et Elham Mohammadi (hessam (point) amini <at> concordia (point) ca)

Concordia University

Le 1er mai 2019 à 11 h 30

Salle 3195, Pavillon André-Aisenstadt


We present our participation to the CLPsych 2019 shared task, under the name CLaC. The goal of the shared task was to detect and assess suicide risk based on a collection of online posts. For our participation, we used an ensemble method which utilizes 8 neural sub-models to extract neural features and predict class probabilities, which are then used by an SVM classifier. Our team ranked first in 2 out of the 3 tasks (tasks A and C).


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