Rule-Based Attractions Describe Paragraph Information Extraction

Xiaolan Feng, Xiaobing Zhao Zhao
{"title":"Rule-Based Attractions Describe Paragraph Information Extraction","authors":"Xiaolan Feng, Xiaobing Zhao Zhao","doi":"10.1109/ICRIS.2018.00103","DOIUrl":null,"url":null,"abstract":"In this paper, a rule-based information extraction method of descriptive paragraphs of scenic spots is proposed. While paying attention to the location information of scenic spots, it extracts brief and general descriptive paragraphs of scenic spots which are taken as descriptive texts of scenic spots, which is of academic reference value for textual information extraction beyond the current entity triple. The experiments are conducted respectively from perspective of the location relation, the affiliation, and the relation of creation of time. When only considering the location relation and rules of the affiliation, the accuracy rate is 90.85%, the recall rate is 85.43%, and the F value is 88.06%. So the validity and applicability of this method are proved.","PeriodicalId":194515,"journal":{"name":"2018 International Conference on Robots & Intelligent System (ICRIS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Robots & Intelligent System (ICRIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRIS.2018.00103","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

In this paper, a rule-based information extraction method of descriptive paragraphs of scenic spots is proposed. While paying attention to the location information of scenic spots, it extracts brief and general descriptive paragraphs of scenic spots which are taken as descriptive texts of scenic spots, which is of academic reference value for textual information extraction beyond the current entity triple. The experiments are conducted respectively from perspective of the location relation, the affiliation, and the relation of creation of time. When only considering the location relation and rules of the affiliation, the accuracy rate is 90.85%, the recall rate is 85.43%, and the F value is 88.06%. So the validity and applicability of this method are proved.
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
基于规则的吸引力描述段落信息提取
本文提出了一种基于规则的景区描述段落信息提取方法。在关注景点位置信息的同时,提取出景点简要概括的描述性段落,作为景点描述性文本,对超越当前实体三重的文本信息提取具有学术参考价值。实验分别从时间的位置关系、隶属关系和创造关系三个角度进行。仅考虑隶属关系的位置关系和规则时,准确率为90.85%,召回率为85.43%,F值为88.06%。从而证明了该方法的有效性和适用性。
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
Design and Implementation of CORDIC Algorithm Based on FPGA Design of Visual Feature Detection System for Intelligent Driving of Electric Vehicle Research and Application of Traffic Sign Detection and Recognition Based on Deep Learning Maritime Intelligent Real-Time Control System Based on UAV Research of Sub-Pixel Inner Diameter Measurement of Workpiece Based on OpenCV
×
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:604180095
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