IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v17y2023i1s1751157722001079.html
   My bibliography  Save this article

Patent landscape and key technology interaction roadmap using graph convolutional network – Case of mobile communication technologies beyond 5G

Author

Listed:
  • Trappey, Amy J.C.
  • Wei, Ann Y.E.
  • Chen, Neil K.T.
  • Li, Kuo-An
  • Hung, L.P.
  • Trappey, Charles V.

Abstract

Beyond 5G (B5G) in mobile network technologies is the latest communication technology currently under development. B5G is expected to achieve superior capabilities in ultra-high network transmission speed, low latency, low energy consumption, and high coverage, comparing to current 5G network performance. Although B5G is still in the development and implementation stage, there are many patents and non-patent literature depicting B5G innovative technologies and applications. The landscapes of B5G technologies are great references for governments and industries to understand the advances in mobile communication for R&D strategies. Thus, this research focuses on developing a formal tech-mining workflow integrating semantic-based patent and non-patent literature analysis for ontology building, patent technological topic clustering, and graph convolutional network (GCN) modeling for depicting key technology interactions among clusters of sub-domain topics. This research emphasizes the study of B5G patent landscape and key technology interaction roadmap in comprehensive steps as a valuable reference for B5G mobile network R&D, as well as for conducting tech-mining of other technology domains of interests.

Suggested Citation

  • Trappey, Amy J.C. & Wei, Ann Y.E. & Chen, Neil K.T. & Li, Kuo-An & Hung, L.P. & Trappey, Charles V., 2023. "Patent landscape and key technology interaction roadmap using graph convolutional network – Case of mobile communication technologies beyond 5G," Journal of Informetrics, Elsevier, vol. 17(1).
  • Handle: RePEc:eee:infome:v:17:y:2023:i:1:s1751157722001079
    DOI: 10.1016/j.joi.2022.101354
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157722001079
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.joi.2022.101354?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhao, Qihang & Feng, Xiaodong, 2022. "Utilizing citation network structure to predict paper citation counts: A Deep learning approach," Journal of Informetrics, Elsevier, vol. 16(1).
    2. Meyer, Martin, 2000. "Does science push technology? Patents citing scientific literature," Research Policy, Elsevier, vol. 29(3), pages 409-434, March.
    3. M.J. Cobo & A.G. López‐Herrera & E. Herrera‐Viedma & F. Herrera, 2011. "Science mapping software tools: Review, analysis, and cooperative study among tools," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(7), pages 1382-1402, July.
    4. An, Jaehyeong & Kim, Kyuwoong & Mortara, Letizia & Lee, Sungjoo, 2018. "Deriving technology intelligence from patents: Preposition-based semantic analysis," Journal of Informetrics, Elsevier, vol. 12(1), pages 217-236.
    5. Robert R. Braam & Henk F. Moed & Anthony F. J. van Raan, 1991. "Mapping of science by combined co‐citation and word analysis. I. Structural aspects," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 42(4), pages 233-251, May.
    6. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
    7. Joung, Junegak & Kim, Kwangsoo, 2017. "Monitoring emerging technologies for technology planning using technical keyword based analysis from patent data," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 281-292.
    8. Min Song & Go Eun Heo & Dahee Lee, 2015. "Identifying the landscape of Alzheimer’s disease research with network and content analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 905-927, January.
    9. M.J. Cobo & A.G. López-Herrera & E. Herrera-Viedma & F. Herrera, 2011. "Science mapping software tools: Review, analysis, and cooperative study among tools," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(7), pages 1382-1402, July.
    10. Pao-Long Chang & Chao-Chan Wu & Hoang-Jyh Leu, 2010. "Using patent analyses to monitor the technological trends in an emerging field of technology: a case of carbon nanotube field emission display," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 5-19, January.
    11. Robert R. Braam & Henk F. Moed & Anthony F. J. van Raan, 1991. "Mapping of science by combined co‐citation and word analysis. II: Dynamical aspects," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 42(4), pages 252-266, May.
    12. Manajit Chakraborty & Maksym Byshkin & Fabio Crestani, 2020. "Patent citation network analysis: A perspective from descriptive statistics and ERGMs," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-28, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. MaruÅ¡a Premru & Matej ÄŒerne & SaÅ¡a BatistiÄ, 2022. "The Road to the Future: A Multi-Technique Bibliometric Review and Development Projections of the Leader–Member Exchange (LMX) Research," SAGE Open, , vol. 12(2), pages 21582440221, May.
    2. Mora, Luca & Deakin, Mark & Reid, Alasdair, 2019. "Combining co-citation clustering and text-based analysis to reveal the main development paths of smart cities," Technological Forecasting and Social Change, Elsevier, vol. 142(C), pages 56-69.
    3. Gaviria-Marin, Magaly & Merigó, José M. & Baier-Fuentes, Hugo, 2019. "Knowledge management: A global examination based on bibliometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 194-220.
    4. Serhat Burmaoglu & Ozcan Saritas, 2019. "An evolutionary analysis of the innovation policy domain: Is there a paradigm shift?," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 823-847, March.
    5. Gallego-Losada, María-Jesús & Montero-Navarro, Antonio & García-Abajo, Elisa & Gallego-Losada, Rocío, 2023. "Digital financial inclusion. Visualizing the academic literature," Research in International Business and Finance, Elsevier, vol. 64(C).
    6. Ying Huang & Wolfgang Glänzel & Lin Zhang, 2021. "Tracing the development of mapping knowledge domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6201-6224, July.
    7. Chen, Xiaoyan & Liu, Yisheng, 2020. "Visualization analysis of high-speed railway research based on CiteSpace," Transport Policy, Elsevier, vol. 85(C), pages 1-17.
    8. Secinaro, Silvana & Calandra, Davide & Lanzalonga, Federico & Ferraris, Alberto, 2022. "Electric vehicles’ consumer behaviours: Mapping the field and providing a research agenda," Journal of Business Research, Elsevier, vol. 150(C), pages 399-416.
    9. Anita Mendiratta & Shveta Singh & Surendra Singh Yadav & Arvind Mahajan, 2023. "Bibliometric and Topic Modeling Analysis of Corporate Social Irresponsibility," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(3), pages 319-339, September.
    10. Sudhir Chandra Das & Sonali Arunima Dhan, 2023. "Trends and Directions of Employee Experience: A Bibliometric Review for Future Research Agenda," Paradigm, , vol. 27(2), pages 172-191, December.
    11. Carlos Sánchez‐Camacho & Rocío Carranza & David Martín‐Consuegra & Estrella Díaz, 2022. "Evolution, trends and future research lines in corporate social responsibility and tourism: A bibliometric analysis and science mapping," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(3), pages 462-476, June.
    12. Wenceslao Arroyo-Machado & Daniel Torres-Salinas & Nicolas Robinson-Garcia, 2021. "Identifying and characterizing social media communities: a socio-semantic network approach to altmetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 9267-9289, November.
    13. Paúl Carrión-Mero & Néstor Montalván-Burbano & Fernando Morante-Carballo & Adolfo Quesada-Román & Boris Apolo-Masache, 2021. "Worldwide Research Trends in Landslide Science," IJERPH, MDPI, vol. 18(18), pages 1-24, September.
    14. Francisco Díez-Martín & Alicia Blanco-González & Camilo Prado-Román, 2021. "The intellectual structure of organizational legitimacy research: a co-citation analysis in business journals," Review of Managerial Science, Springer, vol. 15(4), pages 1007-1043, May.
    15. Irena Sajovic & Bojana Boh Podgornik, 2022. "Bibliometric Analysis of Visualizations in Computer Graphics: A Study," SAGE Open, , vol. 12(1), pages 21582440211, January.
    16. Mehdi Amirkhani & Igor Martek & Mark B. Luther, 2021. "Mapping Research Trends in Residential Construction Retrofitting: A Scientometric Literature Review," Energies, MDPI, vol. 14(19), pages 1-18, September.
    17. Davidescu, Adriana AnaMaria & Petcu, Monica Aureliana & Curea, Stefania Cristina & Manta, Eduard Mihai, 2022. "Two faces of the same coin: Exploring the multilateral perspective of informality in relation to Sustainable Development Goals based on bibliometric analysis," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 683-705.
    18. Shi, Xianwei & Liang, Xingkun & Luo, Yining, 2023. "Unpacking the intellectual structure of ecosystem research in innovation studies," Research Policy, Elsevier, vol. 52(6).
    19. Hafize Nurgul Durmus Senyapar & Murat Akil & Emrah Dokur, 2023. "Adoption of Electric Vehicles: Purchase Intentions and Consumer Behaviors Research in Turkey," SAGE Open, , vol. 13(2), pages 21582440231, June.
    20. Xue Ding & Zhong Yang, 2022. "Knowledge mapping of platform research: a visual analysis using VOSviewer and CiteSpace," Electronic Commerce Research, Springer, vol. 22(3), pages 787-809, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:infome:v:17:y:2023:i:1:s1751157722001079. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.