Knowledge Commons of Institute of Automation,CAS
A Prior Knowledge Based Neural Attention Model for Opioid Topic Identification | |
Yao, Riheng1,2,3; Li, Qiudan1,3; Wei-Hsuan Lo-Ciganic4; Zeng, Daniel Dajun1,2,3 | |
2019-09-05 | |
会议名称 | 2019 IEEE International Conference on Intelligence and Security Informatics (ISI) |
会议日期 | 1-3 July 2019 |
会议地点 | Shenzhen, China |
摘要 | The opioid epidemic has become a serious public health crisis in the United States. Social media sources such as Reddit containing user-generated content may be a valuable safety surveillance platform to evaluate discussions discerning opioid use. This paper proposes a prior knowledge based neural attention model for opioid topics identification, which considers prior knowledge with attention mechanism. Experimental results on a real-world dataset show that our model can extract coherent topics, the identified less discussed but important topics provide more comprehensive information for opioid safety surveillance. |
关键词 | prior knowledge attention opioid topic |
收录类别 | EI |
语种 | 英语 |
七大方向——子方向分类 | 自然语言处理 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39037 |
专题 | 多模态人工智能系统全国重点实验室_互联网大数据与信息安全 |
作者单位 | 1.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences 3.Shenzhen Artificial Intelligence and Data Science Institute 4.Department of Pharmaceutical Outcomes & Policy, University of Florida |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Yao, Riheng,Li, Qiudan,Wei-Hsuan Lo-Ciganic,et al. A Prior Knowledge Based Neural Attention Model for Opioid Topic Identification[C],2019. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
yrh-topic.pdf(124KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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