A RMM Based Word Segmentation Method for Chinese Design Specifications of Building Stairs

Jie-lan Zhang, Yi Chen, Xinhong Hei, Lei Zhu, Qingpan Zhao, Yichuan Wang
{"title":"A RMM Based Word Segmentation Method for Chinese Design Specifications of Building Stairs","authors":"Jie-lan Zhang, Yi Chen, Xinhong Hei, Lei Zhu, Qingpan Zhao, Yichuan Wang","doi":"10.1109/CIS2018.2018.00068","DOIUrl":null,"url":null,"abstract":"With the rapid development of information technology, knowledge graph extracts more and more attentions from researchers. However, Chinese knowledge graph of construction industry is still at the beginning stage, and Chinese word segmentation method, as the basis of natural language processing, plays a vital role on the process of building knowledge graph. In this paper, we study Chinese design specifications of building stairs, and proposes a reverse maximum matching (RMM) based word segmentation method to parse Chinese building specifications. The proposed method first converts the dictionary of building into a hash dictionary. And then, by traversing the design specifications of building stairs, the proposed method handles the non-Chinese symbols in the design specifications. Finally, the proposed method uses RMM algorithm to match contexts with Chinese design specifications and generate the goal results. Through performing experiments on Chinese design specifications of building stairs, the results can be shown that the proposed method is feasible.","PeriodicalId":185099,"journal":{"name":"2018 14th International Conference on Computational Intelligence and Security (CIS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 14th International Conference on Computational Intelligence and Security (CIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS2018.2018.00068","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

With the rapid development of information technology, knowledge graph extracts more and more attentions from researchers. However, Chinese knowledge graph of construction industry is still at the beginning stage, and Chinese word segmentation method, as the basis of natural language processing, plays a vital role on the process of building knowledge graph. In this paper, we study Chinese design specifications of building stairs, and proposes a reverse maximum matching (RMM) based word segmentation method to parse Chinese building specifications. The proposed method first converts the dictionary of building into a hash dictionary. And then, by traversing the design specifications of building stairs, the proposed method handles the non-Chinese symbols in the design specifications. Finally, the proposed method uses RMM algorithm to match contexts with Chinese design specifications and generate the goal results. Through performing experiments on Chinese design specifications of building stairs, the results can be shown that the proposed method is feasible.
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RMM的建筑楼梯中文设计规范分词方法
随着信息技术的飞速发展,知识图谱越来越受到研究者的关注。然而,建筑行业的中文知识图谱还处于起步阶段,而中文分词方法作为自然语言处理的基础,在构建知识图谱的过程中起着至关重要的作用。本文以中文建筑楼梯设计规范为研究对象,提出了一种基于反向最大匹配(RMM)的中文建筑楼梯设计规范分词方法。该方法首先将构建的字典转换为哈希字典。然后,通过遍历建筑楼梯设计规范,对设计规范中的非中文符号进行处理。最后,采用RMM算法将上下文与中文设计规范进行匹配,生成目标结果。通过对我国建筑楼梯设计规范进行试验,结果表明该方法是可行的。
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
A Real-Time Location Privacy Protection Method Based on Space Transformation Cryptanalysis of Kumar's Remote User Authentication Scheme with Smart Card Off-Topic Text Detection Based on Neural Networks Combined with Text Features Research of X Ray Image Recognition Based on Neural Network CFO Algorithm Using Niche and Opposition-Based Learning
×
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