Classifying Patents Based on Their Semantic Content

40 Pages Posted: 31 Jul 2018

See all articles by Antonin Bergeaud

Antonin Bergeaud

HEC Paris - Economics & Decision Sciences

Yoann Potiron

Keio University - Faculty of Business and Commerce

Juste Raimbault

CNRS - UPS CNRS 3611 ISC-PIF

Date Written: June 2018

Abstract

In this paper, we extend some usual techniques of classification resulting from a largescale data-mining and network approach. This new technology, which in particular is designed to be suitable to big data, is used to construct an open consolidated database from raw data on 4 million patents taken from the US patent office from 1976 onward. To build the pattern network, not only do we look at each patent title, but we also examine their full abstract and extract the relevant keywords accordingly. We refer to this classification as semantic approach in contrast with the more common technological approach which consists in taking the topology when considering US Patent office technological classes. Moreover, we document that both approaches have highly different topological measures and strong statistical evidence that they feature a different model. This suggests that our method is a useful tool to extract endogenous information.

Keywords: Patents, Semantic Analysis, Network, Modularity, Innovation, USPTO

JEL Classification: O3, O39

Suggested Citation

Bergeaud, Antonin and Potiron, Yoann and Raimbault, Juste, Classifying Patents Based on Their Semantic Content (June 2018). Banque de France Working Paper No. 685, Available at SSRN: https://ssrn.com/abstract=3222501 or http://dx.doi.org/10.2139/ssrn.3222501

Antonin Bergeaud (Contact Author)

HEC Paris - Economics & Decision Sciences ( email )

Paris
France

Yoann Potiron

Keio University - Faculty of Business and Commerce ( email )

2-15-45 Mita
Minato-ku
Tokyo 108-8345
Japan

Juste Raimbault

CNRS - UPS CNRS 3611 ISC-PIF ( email )

113 rue Nationale
Paris, 75013
France

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