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That’s classified! Inventing a new patent taxonomy
[Text matching to measure patent similarity]

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  • Stephen D Billington
  • Alan J Hanna

Abstract

Innovation researchers currently make use of various patent classification schemas, which are hard to replicate. Using machine learning techniques, we construct a transparent, replicable and adaptable patent taxonomy, and a new automated methodology for classifying patents. We contrast our new schema with existing ones using a long-run historical patent dataset. We find quantitative analyses of patent characteristics are sensitive to the choice of classification; our interpretation of regression coefficients is schema dependent. We suggest much of the innovation literature should be carefully interpreted in light of our findings.

Suggested Citation

  • Stephen D Billington & Alan J Hanna, 2021. "That’s classified! Inventing a new patent taxonomy [Text matching to measure patent similarity]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(3), pages 678-705.
  • Handle: RePEc:oup:indcch:v:30:y:2021:i:3:p:678-705.
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    File URL: http://hdl.handle.net/10.1093/icc/dtaa049
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