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A patent search strategy based on machine learning for the emerging field of service robotics

Author

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  • Kreuchauff, Florian
  • Korzinov, Vladimir

Abstract

Emerging technologies are in the core focus of supra-national innovation policies. These strongly rely on credible data bases for being effective and efficient. However, since emerging technologies are not yet part of any official industry, patent or trademark classification systems, delineating boundaries to measure their early development stage is a nontrivial task. This paper is aimed to present a methodology to automatically classify patents as concerning service robots. We introduce a synergy of a traditional technology identification process, namely keyword extraction and verification by an expert community, with a machine learning algorithm. The result is a novel possibility to allocate patents which (1) reduces expert bias regarding vested interests on lexical query methods, (2) avoids problems with citational approaches, and (3) facilitates evolutionary changes. Based upon a small core set of worldwide service robotics patent applications we derive apt n-gram frequency vectors and train a support vector machine (SVM), relying only on titles, abstracts and IPC categorization of each document. Altering the utilized Kernel functions and respective parameters we reach a recall level of 83% and precision level of 85%.

Suggested Citation

  • Kreuchauff, Florian & Korzinov, Vladimir, 2015. "A patent search strategy based on machine learning for the emerging field of service robotics," Working Paper Series in Economics 71, Karlsruhe Institute of Technology (KIT), Department of Economics and Business Engineering.
  • Handle: RePEc:zbw:kitwps:71
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    References listed on IDEAS

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    1. Graetz, Georg & Michaels, Guy, 2015. "Robots at Work," CEPR Discussion Papers 10477, C.E.P.R. Discussion Papers.
    2. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco.
    3. Bronwyn H. Hall & Adam Jaffe & Manuel Trajtenberg, 2005. "Market Value and Patent Citations," RAND Journal of Economics, The RAND Corporation, pages 16-38.
    4. Adam B. Jaffe & Manuel Trajtenberg & Rebecca Henderson, 1993. "Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations," The Quarterly Journal of Economics, Oxford University Press, pages 577-598.
    5. repec:fth:harver:1473 is not listed on IDEAS
    6. Griliches, Zvi, 1990. "Patent Statistics as Economic Indicators: A Survey," Journal of Economic Literature, American Economic Association, pages 1661-1707.
    7. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    8. Peter Thompson, 2006. "Patent Citations and the Geography of Knowledge Spillovers: Evidence from Inventor- and Examiner-added Citations," The Review of Economics and Statistics, MIT Press, vol. 88(2), pages 383-388, May.
    9. Mogoutov, Andrei & Kahane, Bernard, 2007. "Data search strategy for science and technology emergence: A scalable and evolutionary query for nanotechnology tracking," Research Policy, Elsevier, pages 893-903.
    10. Manfred Fischer & Thomas Scherngell & Eva Jansenberger, 2009. "Geographic localisation of knowledge spillovers: evidence from high-tech patent citations in Europe," The Annals of Regional Science, Springer;Western Regional Science Association, pages 839-858.
    11. Zvi Griliches, 1998. "Patent Statistics as Economic Indicators: A Survey," NBER Chapters,in: R&D and Productivity: The Econometric Evidence, pages 287-343 National Bureau of Economic Research, Inc.
    12. Bresnahan, Timothy, 2010. "General Purpose Technologies," Handbook of the Economics of Innovation, Elsevier.
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    Citations

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    Cited by:

    1. Borissov, Kirill & Pakhnin, Mikhail & Puppe, Clemens, 2017. "On discounting and voting in a simple growth model," European Economic Review, Elsevier, vol. 94(C), pages 185-204.
    2. Betz, Frank & Hautsch, Nikolaus & Peltonen, Tuomas A. & Schienle, Melanie, 2016. "Systemic risk spillovers in the European banking and sovereign network," Journal of Financial Stability, Elsevier, pages 206-224.
    3. Armin Falk & Nora Szech, 2016. "Pleasures of Skill and Moral Conduct," CESifo Working Paper Series 5732, CESifo Group Munich.

    More about this item

    Keywords

    Service Robotics; Search Strategy; Patent Query; Data Mining; Machine Learning; Support Vector Machine;

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

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