QQ客服 官方微博 反馈留言

	Drug Drug Interaction Extraction from Literature Using a Skeleton Long Short Term Memory Neural Network
	Liang Gu; Zhenchao Jiang; Qingshan Jiang
	2017
会议日期	2017
会议地点	美国
英文摘要	Drug Drug Interactions (DDIs) can cause harmful effect. Two shared tasks, DDIExtraction 2011 and DDIExtraction 2013, have been held to promote the implementation and comparative assessment of natural language processing techniques in the field of the pharmacovigilance domain. However, few model can meanwhile achieve state-of-the-art performance on both tasks. A major reason is the lack of representation of DDI instance structure in common. Therefore,in this paper, we propose a novel method to make full use of the DDI structure based on deep learning, in which we grasp the skeleton structure of DDI instances by a skeleton long short term memory (skeleton-LSTM) network. The experimental results show that our method can achieve an F-score of 0.677 on DDIExtraction 2011 and an F-score of 0.714 on DDIExtraction 2013, both of which are state-of-the-art。
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/12689]
专题	深圳先进技术研究院_数字所
作者单位	2017
推荐引用方式 GB/T 7714	Liang Gu,Zhenchao Jiang,Qingshan Jiang. Drug Drug Interaction Extraction from Literature Using a Skeleton Long Short Term Memory Neural Network[C]. 见:. 美国. 2017.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。