That’s classified! Inventing a new patent taxonomy
Text matching to measure patent similarity
Stephen Billington and
Alan J Hanna
Industrial and Corporate Change, 2021, vol. 30, issue 3, 678-705
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.
Date: 2021
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1093/icc/dtaa049 (application/pdf)
Access to full text is restricted to subscribers.
Related works:
Working Paper: That's classified! Inventing a new patent taxonomy (2018) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:oup:indcch:v:30:y:2021:i:3:p:678-705.
Ordering information: This journal article can be ordered from
https://academic.oup.com/journals
Access Statistics for this article
Industrial and Corporate Change is currently edited by Josef Chytry
More articles in Industrial and Corporate Change from Oxford University Press and the Associazione ICC Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK.
Bibliographic data for series maintained by Oxford University Press ().