IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v129y2024i2d10.1007_s11192-023-04712-7.html
   My bibliography  Save this article

A novel text representation which enables image classifiers to also simultaneously classify text, applied to name disambiguation

Author

Listed:
  • Stephen M. Petrie

    (Swinburne University of Technology)

  • T’Mir D. Julius

    (Swinburne University of Technology)

Abstract

We introduce a novel method for converting text data into abstract image representations, which allows image-based processing techniques (e.g. image classification networks) to be applied to text-based comparison problems. We apply the technique to entity disambiguation of inventor names in US patents, obtaining a list of IDs which identify individual inventors with high accuracy. The method involves converting text from each pairwise comparison between two inventor name records into a 2D RGB (stacked) image representation. We then train an image classification neural network to discriminate between such pairwise comparison images. The trained neural network then labels each pair of records as either matched (same inventor) or non-matched (different inventors), producing highly accurate results. Our new text-to-image representation method could also be used more broadly for other text comparison problems, such as entity disambiguation of academic publications, or for problems that require simultaneous classification of both text and image datasets.

Suggested Citation

  • Stephen M. Petrie & T’Mir D. Julius, 2024. "A novel text representation which enables image classifiers to also simultaneously classify text, applied to name disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(2), pages 719-743, February.
    • Handle: RePEc:spr:scient:v:129:y:2024:i:2:d:10.1007_s11192-023-04712-7
    DOI: 10.1007/s11192-023-04712-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-023-04712-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-023-04712-7?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. Bronwyn H. Hall & Adam B. Jaffe & Manuel Trajtenberg, 2001. "The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools," NBER Working Papers 8498, National Bureau of Economic Research, Inc.
    2. Ashish Arora & Michelle Gittelman & Sarah Kaplan & John Lynch & Will Mitchell & Nicolaj Siggelkow & Chunmian Ge & Ke-Wei Huang & Ivan P. L. Png, 2016. "Engineer/scientist careers: Patents, online profiles, and misclassification bias," Strategic Management Journal, Wiley Blackwell, vol. 37(1), pages 232-253, January.
    3. Karin Hoisl, 2009. "Does mobility increase the productivity of inventors?," The Journal of Technology Transfer, Springer, vol. 34(2), pages 212-225, April.
    4. 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.
    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. Stefano Breschi & Francesco Lissoni & Ernest Miguelez, 2017. "Foreign-origin inventors in the USA: testing for diaspora and brain gain effects," Journal of Economic Geography, Oxford University Press, vol. 17(5), pages 1009-1038.
    2. Carlos J. Serrano & Rosemarie Ziedonis, 2018. "How Redeployable are Patent Assets? Evidence from Failed Startups," NBER Working Papers 24526, National Bureau of Economic Research, Inc.
    3. Yang, Chia-Hsuan & Nugent, Rebecca & Fuchs, Erica R.H., 2016. "Gains from others’ losses: Technology trajectories and the global division of firms," Research Policy, Elsevier, vol. 45(3), pages 724-745.
    4. Jordan Bisset & Dirk Czarnitzki & Thorsten Doherr, 2022. "High Skilled Mobility Under Uncertainty," Working Papers of Department of Management, Strategy and Innovation, Leuven 700195, KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven.
    5. Francesco Castellaneta & Raffaele Conti & Aleksandra Kacperczyk, 2017. "Money secrets: How does trade secret legal protection affect firm market value? Evidence from the uniform trade secret act," Strategic Management Journal, Wiley Blackwell, vol. 38(4), pages 834-853, April.
    6. David Autor & David Dorn & Gordon H. Hanson & Gary Pisano & Pian Shu, 2020. "Foreign Competition and Domestic Innovation: Evidence from US Patents," American Economic Review: Insights, American Economic Association, vol. 2(3), pages 357-374, September.
    7. Dorner, Matthias & Harhoff, Dietmar & Gaessler, Fabian & Hoisl, Karin & Poege, Felix, 2019. "Linked Inventor Biography Data 1980-2014 : (INV-BIO ADIAB 8014)," FDZ Datenreport. Documentation on Labour Market Data 201803_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    8. Goossen, Martin C. & Paruchuri, Srikanth, 2022. "Measurement errors and estimation biases with incomplete social networks: replication studies on intra-firm inventor network analysis," Research Policy, Elsevier, vol. 51(1).
    9. David Youngberg & Joshua Hall, 2020. "Inventor Mobility, Human Capital, and the Propensity to Patent," Working Papers 20-10, Department of Economics, West Virginia University.
    10. Le Bas, Christian & Latham, William & Volodin, Dmitry, 2014. "Productivité et mobilité des inventeurs prolifiques : une approche comparative des systèmes d’innovation de quatre grands pays asiatiques (Chine, Corée, Japon, Taiwan)," Revue de la Régulation - Capitalisme, institutions, pouvoirs, Association Recherche et Régulation, vol. 15.
    11. Igna, Ioana A., 2018. "The effects of educational mismatch on inventor productivity. Evidence from Sweden, 2003-2010," Papers in Innovation Studies 2018/8, Lund University, CIRCLE - Centre for Innovation Research.
    12. William Latham & Christian Le Bas & Dmitry Volodin, 2011. "Value of invention, prolific inventor productivity and mobility: evidence from five countries, 1975-2002," Working Papers halshs-00654501, HAL.
    13. Castellani, Davide & Perri, Alessandra & Scalera, Vittoria G., 2022. "Knowledge integration in multinational enterprises: The role of inventors crossing national and organizational boundaries," Journal of World Business, Elsevier, vol. 57(3).
    14. Bisset, Jordan & Czarnitzki, Dirk & Doherr, Thorsten, 2024. "Inventor mobility under uncertainty," Research Policy, Elsevier, vol. 53(1).
    15. Manuel Ammann & Philipp Horsch & David Oesch, 2016. "Competing with Superstars," Management Science, INFORMS, vol. 62(10), pages 2842-2858, October.
    16. Guan-Can Yang & Gang Li & Chun-Ya Li & Yun-Hua Zhao & Jing Zhang & Tong Liu & Dar-Zen Chen & Mu-Hsuan Huang, 2015. "Using the comprehensive patent citation network (CPC) to evaluate patent value," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1319-1346, December.
    17. Pauly, Stefan & Stipanicic, Fernando, 2021. "The creation and diffusion of knowledge: Evidence from the Jet Age," CEPREMAP Working Papers (Docweb) 2112, CEPREMAP.
    18. Suma Athreye & Martha Prevezer, 2008. "R&D offshoring and the domestic science base in India and China," Working Papers 26, Queen Mary, University of London, School of Business and Management, Centre for Globalisation Research.
    19. Florent Silve & Alexander Plekhanov, 2018. "Institutions, innovation and growth : Evidence from industry data," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 26(3), pages 335-362, July.
    20. Ufuk Akcigit & Douglas Hanley & Stefanie Stantcheva, 2022. "Optimal Taxation and R&D Policies," Econometrica, Econometric Society, vol. 90(2), pages 645-684, March.

    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:spr:scient:v:129:y:2024:i:2:d:10.1007_s11192-023-04712-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.