基于依赖树的Web数据中文关系提取

Shanshan Zheng, J. Yang, Xin Lin, Junzhong Gu
{"title":"基于依赖树的Web数据中文关系提取","authors":"Shanshan Zheng, J. Yang, Xin Lin, Junzhong Gu","doi":"10.1109/KICSS.2012.32","DOIUrl":null,"url":null,"abstract":"A new semi-supervised approach for Chinese relation extraction (RE) over constantly growing and edgeless web data is introduced in this paper. Existing semi-supervised approaches have the better improvement potential while lacking syntactic structure and semantic meaning of a sentence and unsuitable to loosely structured Chinese sentences. To follow their basic procedures as well as covering their remaining shortages, a dependency tree (DT) including both structure and semantic information is drawn in. Based on DTs, a new kind of pattern, called DT-based pattern, is proposed to extract new triples. Later patterns are optimized according to the characteristics of Chinese and typed dependency trees. Finally, extensive experiments show the higher precision and more efficiency of the proposed approach against DIPRE.","PeriodicalId":309736,"journal":{"name":"2012 Seventh International Conference on Knowledge, Information and Creativity Support Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Dependency Tree Based Chinese Relation Extraction over Web Data\",\"authors\":\"Shanshan Zheng, J. Yang, Xin Lin, Junzhong Gu\",\"doi\":\"10.1109/KICSS.2012.32\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new semi-supervised approach for Chinese relation extraction (RE) over constantly growing and edgeless web data is introduced in this paper. Existing semi-supervised approaches have the better improvement potential while lacking syntactic structure and semantic meaning of a sentence and unsuitable to loosely structured Chinese sentences. To follow their basic procedures as well as covering their remaining shortages, a dependency tree (DT) including both structure and semantic information is drawn in. Based on DTs, a new kind of pattern, called DT-based pattern, is proposed to extract new triples. Later patterns are optimized according to the characteristics of Chinese and typed dependency trees. Finally, extensive experiments show the higher precision and more efficiency of the proposed approach against DIPRE.\",\"PeriodicalId\":309736,\"journal\":{\"name\":\"2012 Seventh International Conference on Knowledge, Information and Creativity Support Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Seventh International Conference on Knowledge, Information and Creativity Support Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KICSS.2012.32\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Seventh International Conference on Knowledge, Information and Creativity Support Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KICSS.2012.32","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

本文提出了一种新的半监督中文关系抽取方法,用于不断增长的无边界web数据的中文关系抽取。现有的半监督方法具有较好的改进潜力,但缺乏句子的句法结构和语义,不适用于结构松散的汉语句子。为了遵循它们的基本过程并覆盖它们的不足之处,绘制了一个包含结构和语义信息的依赖树(DT)。在此基础上,提出了一种新的三元组提取模式——基于三元组的模式。之后的模式根据中文和类型化依赖树的特点进行了优化。最后,大量的实验表明,该方法具有更高的精度和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dependency Tree Based Chinese Relation Extraction over Web Data
A new semi-supervised approach for Chinese relation extraction (RE) over constantly growing and edgeless web data is introduced in this paper. Existing semi-supervised approaches have the better improvement potential while lacking syntactic structure and semantic meaning of a sentence and unsuitable to loosely structured Chinese sentences. To follow their basic procedures as well as covering their remaining shortages, a dependency tree (DT) including both structure and semantic information is drawn in. Based on DTs, a new kind of pattern, called DT-based pattern, is proposed to extract new triples. Later patterns are optimized according to the characteristics of Chinese and typed dependency trees. Finally, extensive experiments show the higher precision and more efficiency of the proposed approach against DIPRE.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信