Research on the construction and application of event based electromagnetic space big data knowledge graph

Dongsheng Li, Bing Ma, Yuanzhong Ren, K. Li
{"title":"Research on the construction and application of event based electromagnetic space big data knowledge graph","authors":"Dongsheng Li, Bing Ma, Yuanzhong Ren, K. Li","doi":"10.1117/12.2671438","DOIUrl":null,"url":null,"abstract":"In view of the large volume and complex structure of electromagnetic space big data, it is difficult to store and retrieve spectrum data using traditional databases and knowledge graph. Due to the abstractness and space-time characteristics of electromagnetic spectrum data, the use of event forms can better represent the spectrum data, and also make people and machines better understand. Based on the knowledge graph and the concept of events, this paper constructs the spectrum event knowledge graph (EMS-DEKG) and compares several methods of spectrum data retrieval through experiments, which shows that the EMS-DEKG method improves the stability and timeliness of electromagnetic space big data storage and retrieval.","PeriodicalId":227528,"journal":{"name":"International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2671438","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 view of the large volume and complex structure of electromagnetic space big data, it is difficult to store and retrieve spectrum data using traditional databases and knowledge graph. Due to the abstractness and space-time characteristics of electromagnetic spectrum data, the use of event forms can better represent the spectrum data, and also make people and machines better understand. Based on the knowledge graph and the concept of events, this paper constructs the spectrum event knowledge graph (EMS-DEKG) and compares several methods of spectrum data retrieval through experiments, which shows that the EMS-DEKG method improves the stability and timeliness of electromagnetic space big data storage and retrieval.
基于事件的电磁空间大数据知识图谱构建与应用研究
鉴于电磁空间大数据量大、结构复杂,传统的数据库和知识图谱难以对频谱数据进行存储和检索。由于电磁频谱数据的抽象性和空时性,使用事件形式可以更好地表示频谱数据,也可以使人和机器更好地理解。基于知识图谱和事件概念,构建了频谱事件知识图谱(EMS-DEKG),并通过实验对比了几种频谱数据检索方法,结果表明,EMS-DEKG方法提高了电磁空间大数据存储检索的稳定性和时效性。
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 求助全文
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