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/173211/41123] ![]() |
专题 | 模式识别国家重点实验室_自然语言处理 |
通讯作者 | Liu Kang |
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. |
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