中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 计算技术研究所
  3. 中国科学院计算技术研究所
  4. 中国科学院计算技术研究所期刊论文
  5. 英文
Self-learning and embedding based entity alignment

文献类型：期刊论文

作者Cheng, Xueqi1,2; Guan, Saiping1,2; Jin, Xiaolong1,2; Wang, Yuanzhuo1,2; Jia, Yantao1,2; Shen, Huawei1,2; Li, Zixuan1,2
刊名KNOWLEDGE AND INFORMATION SYSTEMS
出版日期2019-05-01
卷号59期号:2页码:361-386
关键词Entity alignment Knowledge graph Self-learning Embedding
ISSN号0219-1377
DOI10.1007/s10115-018-1191-0
英文摘要Entity alignment aims to identify semantical matchings between entities from different groups. Traditional methods (e.g., attribute comparison-based methods, graph operation-based methods and active learning ones) are usually supervised by labeled data as prior knowledge. Since it is not trivial to label data for training, researchers have then turned to unsupervised methods, and have thus developed similarity-based methods, probabilistic methods, graphical model-based methods, etc. In addition, structure or class information is further explored. As an important part of a knowledge graph, entities contain rich semantical information that can be well learned by knowledge graph embedding methods in low-dimensional vector spaces. However, existing methods for entity alignment have paid little attention to knowledge graph embedding. In this paper, we propose a self-learning and embedding based method for entity alignment, thus called SEEA, to iteratively find semantically aligned entity pairs, which makes full use of semantical information contained in the attributes of entities. Experiments on three realistic datasets and comparison with a few baseline methods validate the effectiveness and merits of the proposed method.
资助项目National Key Research and Development Program of China[2016YFB1000902] ; National Key Research and Development Program of China[2017YFC0820404] ; National Natural Science Foundation of China[61772501] ; National Natural Science Foundation of China[61572473] ; National Natural Science Foundation of China[61572469] ; National Natural Science Foundation of China[91646120]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000461572500005
出版者SPRINGER LONDON LTD
源URL[http://119.78.100.204/handle/2XEOYT63/4143]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Jin, Xiaolong
作者单位1.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, CAS Key Lab Network Data Sci & Technol, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Cheng, Xueqi,Guan, Saiping,Jin, Xiaolong,et al. Self-learning and embedding based entity alignment[J]. KNOWLEDGE AND INFORMATION SYSTEMS,2019,59(2):361-386.
APA Cheng, Xueqi.,Guan, Saiping.,Jin, Xiaolong.,Wang, Yuanzhuo.,Jia, Yantao.,...&Li, Zixuan.(2019).Self-learning and embedding based entity alignment.KNOWLEDGE AND INFORMATION SYSTEMS,59(2),361-386.
MLA Cheng, Xueqi,et al."Self-learning and embedding based entity alignment".KNOWLEDGE AND INFORMATION SYSTEMS 59.2(2019):361-386.

入库方式： OAI收割

来源：计算技术研究所

浏览0
下载0
收藏0
其他版本

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。