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Singling out individual inventors from patent data

Author

Listed:
  • Ernest Miguélez

    (AQR-IREA. Department of Econometrics, Statistics and Spanish Economy. University of Barcelona, Av. Diagonal 690, 08034 Barcelona, Spain)

  • Ismael Gómez-Miguélez

    (Signal Theory and Communications Department. Technical University of Catalonia, c/ Jordi Girona 1-3, 08034 Barcelona, Spain.)

Abstract

An increasing number of studies have sprung up in recent years seeking to identify individual inventors from patent data. Different heuristics have been suggested to use their names and other information disclosed in patent documents in order to find out “who is who” in patents. This paper contributes to this literature by setting forth a methodology to identify them using patents applied to the European Patent Office (EPO hereafter). As in the large part of this literature, we basically follow a three-steps procedure: (1) the parsing stage, aimed at reducing the noise in the inventor’s name and other fields of the patent; (2) the matching stage, where name matching algorithms are used to group possible similar names; (3) the filtering stage, where additional information and different scoring schemes are used to filter out these potential same inventors. The paper includes some figures resulting of applying the algorithms to the set of European inventors applying to the EPO for a large period of time.

Suggested Citation

  • Ernest Miguélez & Ismael Gómez-Miguélez, 2011. "Singling out individual inventors from patent data," Working Papers XREAP2011-03, Xarxa de Referència en Economia Aplicada (XREAP), revised May 2011.
  • Handle: RePEc:xrp:wpaper:xreap2011-03
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    File URL: http://www.xreap.cat/RePEc/xrp/pdf/XREAP2011-03.pdf
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    Cited by:

    1. Ventura, Samuel L. & Nugent, Rebecca & Fuchs, Erica R.H., 2015. "Seeing the non-stars: (Some) sources of bias in past disambiguation approaches and a new public tool leveraging labeled records," Research Policy, Elsevier, vol. 44(9), pages 1672-1701.

    More about this item

    Keywords

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    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • J61 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Geographic Labor Mobility; Immigrant Workers
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • R0 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General

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