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2018 EMNLP EMNLP 2018

CLaC at SMM4H Task 1, 2, and 4

Abstract

AbstractCLaC Labs participated in Tasks 1, 2, and 4 using the same base architecture for all tasks with various parameter variations. This was our first exploration of this data and the SMM4H Tasks, thus a unified system was useful to compare the behavior of our architecture over the different datasets and how they interact with different linguistic features.

🌉 Interdisciplinary Bridge — Deep Learning and Healthcare & Medicine and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — smm4h task
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Parsa Bagherzadeh , Nadia Sheikh , Sabine Bergler

Topics

Machine Learning > Core Methods > Classification Machine Learning > Application Areas > Domain Adaptation Natural Language Processing > Applications > Text Classification Healthcare & Medicine > Research > Medical AI Deep Learning > Learning Types > Deep Learning

Keywords

text classification linguistic feature social media mining health nlp neural network smm4h task base architecture parameter variation
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