تقرير
NRC-Canada at SMM4H Shared Task: Classifying Tweets Mentioning Adverse Drug Reactions and Medication Intake
| العنوان: | NRC-Canada at SMM4H Shared Task: Classifying Tweets Mentioning Adverse Drug Reactions and Medication Intake |
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| المؤلفون: | Kiritchenko, Svetlana, Mohammad, Saif M., Morin, Jason, de Bruijn, Berry |
| سنة النشر: | 2018 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language |
| الوصف: | Our team, NRC-Canada, participated in two shared tasks at the AMIA-2017 Workshop on Social Media Mining for Health Applications (SMM4H): Task 1 - classification of tweets mentioning adverse drug reactions, and Task 2 - classification of tweets describing personal medication intake. For both tasks, we trained Support Vector Machine classifiers using a variety of surface-form, sentiment, and domain-specific features. With nine teams participating in each task, our submissions ranked first on Task 1 and third on Task 2. Handling considerable class imbalance proved crucial for Task 1. We applied an under-sampling technique to reduce class imbalance (from about 1:10 to 1:2). Standard n-gram features, n-grams generalized over domain terms, as well as general-domain and domain-specific word embeddings had a substantial impact on the overall performance in both tasks. On the other hand, including sentiment lexicon features did not result in any improvement. Comment: In Proceedings of the Social Media Mining for Health Applications Workshop at AMIA-2017, Washington, DC, USA, 2017 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1805.04558 |
| رقم الأكسشن: | edsarx.1805.04558 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |