A Prior Knowledge Based Neural Attention Model for Opioid Topic Identification | |
Yao, Riheng2,3,4; Li, Qiudan2,4; Wei-Hsuan Lo-Ciganic1; Zeng, Daniel Dajun2,3,4 | |
2019-09-05 | |
会议日期 | 1-3 July 2019 |
会议地点 | Shenzhen, China |
关键词 | prior knowledge attention opioid topic |
英文摘要 | 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. |
语种 | 英语 |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/39037] |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_互联网大数据与安全信息学研究中心 |
作者单位 | 1.Department of Pharmaceutical Outcomes & Policy, University of Florida 2.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences 3.University of Chinese Academy of Sciences 4.Shenzhen Artificial Intelligence and Data Science Institute |
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]. 见:. Shenzhen, China. 1-3 July 2019. |
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