Metaverse: technology landscape of patent informations

E. Moresi, Isabel Pinho, António Pedro Costa
{"title":"Metaverse: technology landscape of patent informations","authors":"E. Moresi, Isabel Pinho, António Pedro Costa","doi":"10.23919/CISTI58278.2023.10211453","DOIUrl":null,"url":null,"abstract":"Technically, the metaverse is a shared virtual collective space created by converging virtually enhanced physical and digital reality. As a combinatorial innovation, multiple technologies and trends are required, such as virtual reality, augmented reality, the internet of things, 5G, and artificial intelligence. The objective of this paper is to present a landscape of the technologies registered in patent documents using the R Bibliometrix package to explore the metadata retrieved in the research. The methodology of this work comprises the data collection, detailing how the study was carried out, and the analysis of the patent metadata using the R-Bibliometrix package. The technology landscape contained the performance and technological structure analyses. The performance indicators identified patents by jurisdiction and top applicants. The technological structure presented the following topics: the most frequent words and CPC/subclass codes; trend topics; thematic map and evolution of the CPC/group codes. The conclusion highlights the use of R-Bibliometrix for the development of a technological landscape.","PeriodicalId":121747,"journal":{"name":"2023 18th Iberian Conference on Information Systems and Technologies (CISTI)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 18th Iberian Conference on Information Systems and Technologies (CISTI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/CISTI58278.2023.10211453","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

Technically, the metaverse is a shared virtual collective space created by converging virtually enhanced physical and digital reality. As a combinatorial innovation, multiple technologies and trends are required, such as virtual reality, augmented reality, the internet of things, 5G, and artificial intelligence. The objective of this paper is to present a landscape of the technologies registered in patent documents using the R Bibliometrix package to explore the metadata retrieved in the research. The methodology of this work comprises the data collection, detailing how the study was carried out, and the analysis of the patent metadata using the R-Bibliometrix package. The technology landscape contained the performance and technological structure analyses. The performance indicators identified patents by jurisdiction and top applicants. The technological structure presented the following topics: the most frequent words and CPC/subclass codes; trend topics; thematic map and evolution of the CPC/group codes. The conclusion highlights the use of R-Bibliometrix for the development of a technological landscape.
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
虚拟世界:专利信息的技术景观
从技术上讲,虚拟世界是一个共享的虚拟集体空间,由虚拟增强的物理和数字现实融合而成。作为组合创新,需要虚拟现实、增强现实、物联网、5G、人工智能等多种技术和趋势。本文的目的是使用R Bibliometrix软件包来探索研究中检索到的元数据,以呈现专利文件中注册的技术的景观。这项工作的方法包括数据收集,详细说明研究是如何进行的,以及使用R-Bibliometrix软件包分析专利元数据。技术景观包括性能分析和技术结构分析。绩效指标根据司法管辖区和顶级申请人确定专利。技术结构呈现以下主题:最常见的词和CPC/子类代码;趋势主题;主题图及CPC/组别代码的演变。结论强调了R-Bibliometrix在技术景观发展中的应用。
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
Towards a Stochastic SEIR Model for the COVID-19 Post-Pandemic Scenario Possibility of building a fuzzy epistemology from fuzzy logic presuppositions Act Against the Aggression : A Preliminary Model of a Digital Platform Aimed at Cyberaggressions in the Portuguese University Environment Performability Model for the Medium Priority Transport Systems Predicting Low Birth Weight Using Machine Learning Models
×
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