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Applications and development of artificial intelligence system from the perspective of system science

A bibliometric review

Bibliographic Data

ID21652145
AuthorsHong Jiang (0000-0002-9299-5484, School of Business and Management Jilin University Changchun China), Jinlong Gai (0000-0003-1039-9345, School of Business and Management Jilin University Changchun China), Shukuan Zhao (School of Business and Management Jilin University Changchun China, corresponding author), Peggy E Chaudhry (0000-0002-9833-0395, Villanova School of Business Villanova University Villanova Pennsylvania USA), Sohail S Chaudhry (0000-0002-6688-3884, Villanova School of Business Villanova University Villanova Pennsylvania USA)
Year2022
Volume39
Issue3
Pages361-378
Publication date2022-05-01
Open AccessYes
TypeARTICLE
VenueSystems Research and Behavioral Science (JOURNAL)
Journal identifiersISSN: 1092-7026 • E-ISSN: 1099-1743
PublisherWiley (PUBLISHER • GB)
DOI10.1002/sres.2865
OpenAlexW4281770712
LanguageEN
Citations received4
References cited105

With the rapid development of big data, 6G, Internet of Things (IoT) and other information and communication technologies (ICTs), artificial intelligence (AI) has ushered in new opportunities for more advancements. AI systems are changing the survival and development of human society. This study focuses on the research and application of AI systems within the scientific framework of systems thinking. From scientometrics, this study adopts cocitation analysis and keywords co‐occurrence analysis to sort existing applications of AI system to research network and research overview while giving the current research hotspots of AI system application research. Concurrently, the development trend and direction of AI systems are analysed, and the opportunities and challenges faced are put forward, which lays a foundation for system research in the field of AI systems

Big data · Data mining · Data science · Knowledge management · Scientometrics · World Wide Web · Big Data and Business Intelligence · Computer Science · Digital Transformation in Industry · Explainable Artificial Intelligence (XAI · Artificial Intelligence

  • Exploring the relationships between Industry 4.0 implementation factors through systems thinking and network analysis

    Open Access•Christian Hoyer, Indra Gunawan et al.•Systems Research and Behavioral…•2023

  • Systems research on artificial intelligence

    Open Access•Li Da Xu•Systems Research and Behavioral…•2022

  • Metaverse and Artificial Intelligence as Web 4.0

    Open Access•Anton Klarin, Elena Gorenskaia et al.•Systems Research and Behavioral…•2026

  • Professionalism in artificial intelligence

    Open Access•Anton Klarin, Hossein Ali Abadi et al.•Systems Research and Behavioral…•2024

  • Learning representations by back-propagating errors

    Open Access•David E Rumelhart, Geoffrey E Hinton et al.•Nature•1986

  • Field-normalized citation impact indicators and the choice of an appropriate counting method

    Open Access•Ludo Waltman, Nees Jan van Eck•Journal of Informetrics•2015

  • The perceptron

    Frank F Rosenblatt, F Rosenblatt•Psychological Review•1958

  • Support-Vector Networks

    Open Access•Corinna Cortes, Vladimir Vapnik•Machine Learning•1995

  • Gradient-based learning applied to document recognition

    Open Access•Yann LeCun, Léon Bottou et al.•Proceedings of the IEEE•1998

  • A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting

    Open Access•Yoav Freund, Robert E Schapire•Journal of Computer and System…•1997

  • Visualizing Bibliometric Networks

    Open Access•Nees Jan van Eck, Ludo Waltman•Measuring Scholarly Impact•2014

  • Constructing bibliometric networks

    Open Access•Antonio Perianes‐Rodríguez, Antonio Perianes-Rodriguez et al.•Journal of Informetrics•2016

  • A Fast Learning Algorithm for Deep Belief Nets

    Geoffrey E Hinton, Simon Osindero et al.•Neural Computation•2006

  • Co‐citation in the scientific literature

    Open Access•Henry Small•Journal of the American Society…•1973

  • Bagging predictors

    Open Access•Leo Breiman•Machine Learning•1996

  • Long Short-Term Memory

    Sepp Hochreiter, Jurgen Schmidhuber•Neural Computation•1997

  • Random Forests

    Open Access•Leo Breiman•Machine Learning•2001

  • Deep learning

    Open Access•Yann LeCun, Yoshua Bengio et al.•Nature•2015

  • Towards a Methodology for Developing Evidence‐Informed Management Knowledge by Means of Systematic Review

    Open Access•David Tranfield, David Denyer et al.•British Journal of Management•2003

  • Drilling down the viable system theories in business, management and accounting

    Open Access•Francesca Iandolo, Pietro Vito et al.•Systems Research and Behavioral…•2021

  • The Implementation of Industry 4.0 – A Systematic Literature Review of the Key Factors

    Open Access•Christian Hoyer, Indra Gunawan et al.•Systems Research and Behavioral…•2020

  • Taxonomy of Industry 4.0 research

    Open Access•Dashi Nazarov, D Yu Nazarov et al.•Systems Research and Behavioral…•2020

  • Special issue on system research on artificial intelligence

    Open Access•Li Da Xu•Systems Research and Behavioral…•2021

  • Software survey

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Citations per year1
Citation span2022 - 2026 (5)
Highly citedNo

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