题名 | Find a Reasonable Ending for Stories: Does Logic Relation Help the Story Cloze Test? |
作者 | |
通讯作者 | Yan, Rui |
发表日期 | 2019
|
会议录名称 | |
页码 | 10031-10032
|
出版地 | 2275 E BAYSHORE RD, STE 160, PALO ALTO, CA 94303 USA
|
出版者 | |
摘要 | Natural language understanding is a challenging problem that covers a wide range of tasks. While previous methods generally train each task separately, we consider combining the cross-task features to enhance the task performance. In this paper, we incorporate the logic information with the help of the Natural Language Inference (NLI) task to the Story Cloze Test (SCT). Previous work on SCT considered various semantic information, such as sentiment and topic, but lack the logic information between sentences which is an essential element of stories. Thus we propose to extract the logic information during the course of the story to improve the understanding of the whole story. The logic information is modeled with the help of the NLI task. Experimental results prove the strength of the logic information. |
学校署名 | 其他
|
语种 | 英语
|
相关链接 | [来源记录] |
收录类别 | |
资助项目 | NSFC[61672058]
; NSFC[61876196]
|
WOS研究方向 | Computer Science
; Engineering
|
WOS类目 | Computer Science, Artificial Intelligence
; Computer Science, Theory & Methods
; Engineering, Electrical & Electronic
|
WOS记录号 | WOS:000486572504153
|
EI入藏号 | 20203509101318
|
EI主题词 | Artificial intelligence
; Computer circuits
|
EI分类号 | Computer Circuits:721.3
; Artificial Intelligence:723.4
|
来源库 | Web of Science
|
引用统计 |
被引频次[WOS]:1
|
成果类型 | 会议论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/42219 |
专题 | 南方科技大学 工学院_计算机科学与工程系 |
作者单位 | 1.Peking Univ, Inst Comp Sci & Technol, Beijing, Peoples R China 2.Univ Queensland, Brisbane, Qld, Australia 3.Peking Univ, Ctr Data Sci, Beijing, Peoples R China 4.Southern Univ Sci & Technol, Shenzhen, Peoples R China |
推荐引用方式 GB/T 7714 |
Shang, Mingyue,Fu, Zhenxin,Yin, Hongzhi,et al. Find a Reasonable Ending for Stories: Does Logic Relation Help the Story Cloze Test?[C]. 2275 E BAYSHORE RD, STE 160, PALO ALTO, CA 94303 USA:ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE,2019:10031-10032.
|
条目包含的文件 | 条目无相关文件。 |
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