The recognition of Laos organization name based on a cascaded conditional random fields

Shaopeng Duan, Lanjiang Zhou, Feng Zhou
{"title":"The recognition of Laos organization name based on a cascaded conditional random fields","authors":"Shaopeng Duan, Lanjiang Zhou, Feng Zhou","doi":"10.1109/CITS.2016.7546439","DOIUrl":null,"url":null,"abstract":"The recognition of Laos organization name is a difficult problem in the entity recognition of Laos language. This paper presents a algorithm of Laos organization name recognition model based on cascaded conditional random fields. The algorithm solved the recognition of easy entity such as person name and location name in the lower model of conditional random fields(CRFs) and served the recognition of complicated organization names on the higher CRFs. This paper designed a efficient feature template and automatic feature selection algorithm for the conditional random fields model of organization names. In the open test of a mass linguistic data, the recall rate reached 79.67%, precision rate reached 77.72%, F - measure reached 78.68%.","PeriodicalId":340958,"journal":{"name":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CITS.2016.7546439","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The recognition of Laos organization name is a difficult problem in the entity recognition of Laos language. This paper presents a algorithm of Laos organization name recognition model based on cascaded conditional random fields. The algorithm solved the recognition of easy entity such as person name and location name in the lower model of conditional random fields(CRFs) and served the recognition of complicated organization names on the higher CRFs. This paper designed a efficient feature template and automatic feature selection algorithm for the conditional random fields model of organization names. In the open test of a mass linguistic data, the recall rate reached 79.67%, precision rate reached 77.72%, F - measure reached 78.68%.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于级联条件随机场的老挝组织名称识别
老挝组织名称的识别是老挝语实体识别中的一个难题。提出了一种基于级联条件随机场的老挝组织名称识别模型算法。该算法在条件随机场的低阶模型上解决人名、地名等简单实体的识别问题,在高阶模型上解决复杂机构名称的识别问题。针对组织名称的条件随机场模型,设计了一种高效的特征模板和自动特征选择算法。在海量语言数据的公开测试中,查全率达到79.67%,查准率达到77.72%,F - measure达到78.68%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Recursive construction of quasi-cyclic cycle LDPC codes based on replacement products Design and realization of IMA/DIMA system management based on avionics switched network Mining co-location patterns with spatial distribution characteristics Multilayer perceptron for modulation recognition cognitive radio system Joint hierarchical modulation and network coding for asymmetric data transmission in wireless cooperative communication
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1