注射与否:疫苗接种行为检测的NLP方法比较

Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task Pub Date : 2018-10-01 DOI:10.18653/v1/W18-5911

Aditya Joshi, Xiang Dai, Sarvnaz Karimi, R. Sparks, Cécile Paris, C. Macintyre

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引用次数: 17

摘要

疫苗接种行为检测涉及预测一个人是否接受或即将接受疫苗。我们在SMM4H研讨会上提交了疫苗接种行为检测共享任务。我们的发现基于三种流行的文本分类方法:基于规则的、基于统计的和基于深度学习的。我们的最终提交是:(1)使用词汇、语言处理工具和词嵌入衍生出具有特定任务特征的统计分类器的集合;(2)使用预训练语言模型的LSTM分类器。

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Shot Or Not: Comparison of NLP Approaches for Vaccination Behaviour Detection

Vaccination behaviour detection deals with predicting whether or not a person received/was about to receive a vaccine. We present our submission for vaccination behaviour detection shared task at the SMM4H workshop. Our findings are based on three prevalent text classification approaches: rule-based, statistical and deep learning-based. Our final submissions are: (1) an ensemble of statistical classifiers with task-specific features derived using lexicons, language processing tools and word embeddings; and, (2) a LSTM classifier with pre-trained language models.

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Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task

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