Employing External Rich Knowledge for Machine Comprehension

	Employing External Rich Knowledge for Machine Comprehension
	Wang Bingning; Guo Shangmin; Liu Kang; He Shizhu; Zhao Jun
	2016
会议日期	2016-7
会议地点	美国纽约
关键词	Machine Comprehension Question Answering Deep Learning
页码	2929-2935
英文摘要	Recently proposed machine comprehension (MC) applicationisanefforttodealwithnaturallanguage understanding problem. However, the small size of machine comprehension labeled data confines the application of deep neural networks architectures that have shown advantage in semantic inference tasks. Previous methods use a lot of NLP tools to extract linguistic features but only gain little improvement over simple baseline. In this paper, we build an attention-based recurrent neural network model, train it with the help of external knowledge which is semantically relevant to machine comprehension, and achieves a new state-of-the-art result.
语种	英语
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/20206]
专题	自动化研究所_模式识别国家重点实验室_自然语言处理团队
通讯作者	Liu Kang
作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Wang Bingning,Guo Shangmin,Liu Kang,et al. Employing External Rich Knowledge for Machine Comprehension[C]. 见:. 美国纽约. 2016-7.