Big Data and Technology Evolution in the IoT Industry

IF 0.6 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Biometrics Pub Date : 2020-09-24 DOI:10.5539/IJBM.V15N10P94
Elona Marku, Maryia Zaitsava, Manuel Castriotta, M. Guardo, M. Loi
{"title":"Big Data and Technology Evolution in the IoT Industry","authors":"Elona Marku, Maryia Zaitsava, Manuel Castriotta, M. Guardo, M. Loi","doi":"10.5539/IJBM.V15N10P94","DOIUrl":null,"url":null,"abstract":"The present study aims to better understand how and to what extent the different dimensions of Big Data can offer insights on technology evolution. By using a patent analytics perspective, in this paper, we introduce a novel approach based on co-words analysis using the abstracts of 170,279 European patents in the Internet of Things (IoT) field published from 2011 to 2019. In so doing, we map and visualize an industry’s technology structure, development, and trends, as well as disentangle the IoT technology conceptual structure, highlighting its core and boundary concepts. This is the first study that applies a decomposition framework to clarify the determinants of IoT inventions, showing relevant changes in the focus of IoT technology overtime. By shedding light on the evolutionary dynamics of the field, this research offers a valuable contribution to the technology innovation literature.","PeriodicalId":54064,"journal":{"name":"International Journal of Biometrics","volume":"48 1","pages":"94"},"PeriodicalIF":0.6000,"publicationDate":"2020-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Biometrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5539/IJBM.V15N10P94","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

The present study aims to better understand how and to what extent the different dimensions of Big Data can offer insights on technology evolution. By using a patent analytics perspective, in this paper, we introduce a novel approach based on co-words analysis using the abstracts of 170,279 European patents in the Internet of Things (IoT) field published from 2011 to 2019. In so doing, we map and visualize an industry’s technology structure, development, and trends, as well as disentangle the IoT technology conceptual structure, highlighting its core and boundary concepts. This is the first study that applies a decomposition framework to clarify the determinants of IoT inventions, showing relevant changes in the focus of IoT technology overtime. By shedding light on the evolutionary dynamics of the field, this research offers a valuable contribution to the technology innovation literature.
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
物联网产业中的大数据与技术演进
本研究旨在更好地理解大数据的不同维度如何以及在多大程度上为技术发展提供见解。本文从专利分析的角度,利用2011 - 2019年欧洲物联网(IoT)领域发表的170,279项专利摘要,提出了一种基于共词分析的新方法。在此过程中,我们绘制和可视化了一个行业的技术结构、发展和趋势,并理清了物联网技术的概念结构,突出了其核心和边界概念。这是第一个应用分解框架来澄清物联网发明的决定因素的研究,显示了物联网技术重点随着时间的推移而发生的相关变化。通过揭示该领域的进化动态,本研究为技术创新文献提供了宝贵的贡献。
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
International Journal of Biometrics
International Journal of Biometrics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
1.50
自引率
0.00%
发文量
46
期刊介绍: Biometrics and human biometric characteristics form the basis of research in biological measuring techniques for the purpose of people identification and recognition. IJBM addresses the fundamental areas in computer science that deal with biological measurements. It covers both the theoretical and practical aspects of human identification and verification.
期刊最新文献
A Secure Finger vein Recognition System using WS-Progressive GAN and C4 Classifier Exemplar-Based Facial Attribute Manipulation: A Review Arabic Offline writer identification on a new version of AHTID/MW database Recent trends and challenges in human computer interaction using automatic emotion recognition: a review Iris Recognition System Using Deep Learning Techniques
×
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