A4 Article in conference proceedings
Ensemble of Convolutional Neural Networks for Medicine Intake Recognition in Twitter




List of Authors: Kai Hakala, Farrokh Mehryary, Hans Moen, Suwisa Kaewphan, Tapio Salakoski, Filip Ginter
Publication year: 2017
Journal: CEUR Workshop Proceedings
Book title *: Proceedings of the 2nd Social Media Mining for Health Research and Applications Workshop (SMM4H 2017)
Title of series: CEUR Workshop Proceedings
Volume number: 1996
Number of pages: 5
ISSN: 1613-0073

Abstract

We present the results from our participation in the 2nd Social Media Mining for Health Applications Shared Task –
Task 2. The goal of this task is to develop systems capable of recognizing mentions of medication intake in Twitter.
Our best performing classification system is an ensemble of neural networks with features generated by word- and
character-level convolutional neural network channels and a condensed weighted bag-of-words representation. A
relatively strong performance is achieved, with an F-score of 66.3 according to the official evaluation, resulting in the
5th place in the shared task with performance close to the best systems created by other participating teams.


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Last updated on 2019-29-01 at 11:04