中国科学院自动化研究所机构知识库
Advanced  
CASIA OpenIR  > 数字内容技术与服务研究中心  > 超级计算大脑团队  > 期刊论文
题名: A neural network framework for relation extraction: Learning entity semantic and relation pattern
作者: Zheng Suncong(郑孙聪)1; Xu, Jiaming1; Zhou, Peng1; Bao Hongyun(包红云)1; Qi, Zhenyu1; Xu, Bo1, 2
刊名: KNOWLEDGE-BASED SYSTEMS
出版日期: 2016-12-15
卷号: 114, 期号:1, 页码:12-23
关键词: Relation extraction ; Deep neural network ; Convolutional neural network ; Entity embedding ; Keywords extraction
DOI: 10.1016/j.knosys.2016.09.019
通讯作者: bao hongyun
文章类型: Article
英文摘要: Relation extraction is to identify the relationship of two given entities in the text. It is an important step in the task of knowledge extraction. Most conventional methods for the task of relation extraction focus on designing effective handcrafted features or learning a semantic representation of the whole sentence. Sentences with the same relationship always share the similar expressions. Besides, the semantic properties of given entities can also help to distinguish some confusing relations. Based on the above observations, we propose a neural network based framework for relation classification. It can simultaneously learn the relation pattern's information and the semantic properties of given entities. In this framework, we explore two specific models: the CNN-based model and LSTM-based model. We conduct experiments on two public datasets: the SemEval-2010 Task8 dataset and the ACE05 dataset. The proposed method achieves the state-of-the-art result without using any external information. Additionally, the experimental results also show that our approach can represent the semantic relationship of the given entities effectively. (C) 2016 Elsevier B.V. All rights reserved.
WOS标题词: Science & Technology ; Technology
类目[WOS]: Computer Science, Artificial Intelligence
研究领域[WOS]: Computer Science
收录类别: SCI
项目资助者: National High Technology Research and Development Program of China (863 Program)(2015AA015402) ; Strategic Priority Research Program of the Chinese Academy of Sciences(XDB02070005) ; National Natural Science Foundation(71402178 ; 61602479)
语种: 英语
WOS记录号: WOS:000389396800002
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.ia.ac.cn/handle/173211/12344
Appears in Collections:数字内容技术与服务研究中心_超级计算大脑团队_期刊论文

Files in This Item: Download All
File Name/ File Size Content Type Version Access License
kbs.pdf(1872KB)期刊论文作者接受稿开放获取View Download

作者单位: 1.Chinese Acad Sci, Inst Automat, Beijing 100864, Peoples R China
2.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China

Recommended Citation:
Suncong Zheng,Jiaming Xu,Peng Zhou,et al. A neural network framework for relation extraction: Learning entity semantic and relation pattern[J]. knowledge-based Systems,2016(1):1-12.
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Zheng, Suncong]'s Articles
[Xu, Jiaming]'s Articles
[Zhou, Peng]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Zheng, Suncong]‘s Articles
[Xu, Jiaming]‘s Articles
[Zhou, Peng]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
文件名: kbs.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!
Copyright © 2007-2017  中国科学院自动化研究所 - Feedback
Powered by CSpace