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Mapping patent classifications: portfolio and statistical analysis, and the comparison of strengths and weaknesses

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  • Loet Leydesdorff

    (University of Amsterdam)

  • Dieter Franz Kogler

    (University College Dublin)

  • Bowen Yan

    (Singapore University of Technology and Design)

Abstract

The Cooperative Patent Classifications (CPC) recently developed cooperatively by the European and US Patent Offices provide a new basis for mapping patents and portfolio analysis. CPC replaces International Patent Classifications (IPC) of the World Intellectual Property Organization. In this study, we update our routines previously based on IPC for CPC and use the occasion for rethinking various parameter choices. The new maps are significantly different from the previous ones, although this may not always be obvious on visual inspection. We provide nested maps online and a routine for generating portfolio overlays on the maps; a new tool is provided for “difference maps” between patent portfolios of organizations or firms. This is illustrated by comparing the portfolios of patents granted to two competing firms—Novartis and MSD—in 2016. Furthermore, the data is organized for the purpose of statistical analysis.

Suggested Citation

  • Loet Leydesdorff & Dieter Franz Kogler & Bowen Yan, 2017. "Mapping patent classifications: portfolio and statistical analysis, and the comparison of strengths and weaknesses," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1573-1591, September.
    • Handle: RePEc:spr:scient:v:112:y:2017:i:3:d:10.1007_s11192-017-2449-0
    DOI: 10.1007/s11192-017-2449-0
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    5. Choi, Seokkyu & Lee, Hyeonju & Park, Eunjeong & Choi, Sungchul, 2022. "Deep learning for patent landscaping using transformer and graph embedding," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    6. Loet Leydesdorff, 2018. "Diversity and interdisciplinarity: how can one distinguish and recombine disparity, variety, and balance?," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 2113-2121, September.
    7. Nomaler, Önder & Verspagen, Bart, 2021. "Patent landscaping using 'green' technological trajectories," MERIT Working Papers 2021-005, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    8. Wang, Zhinan & Porter, Alan L. & Wang, Xuefeng & Carley, Stephen, 2019. "An approach to identify emergent topics of technological convergence: A case study for 3D printing," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 723-732.
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    11. Seunghyun Oh & Jaewoong Choi & Namuk Ko & Janghyeok Yoon, 2020. "Predicting product development directions for new product planning using patent classification-based link prediction," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1833-1876, December.
    12. Konstantina Sdravopoulou & Juan Manuel Muñoz González & María Dolores Hidalgo-Ariza, 2021. "Educating Adults with a Location-Based Augmented Reality Game: A Content Analysis Approach," Mathematics, MDPI, vol. 9(17), pages 1-16, August.
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