Patent Similarity Data and Innovation Metrics

Northwestern University - McCormick School of Engineering and Applied Science; Northwestern University; Northwestern University; Northwestern University

Date Written: July 21, 2020

Abstract

We introduce and describe the Patent Similarity Data set, comprising vector space model-based similarity scores for United States utility patents. The data set provides approximately 640 million pre-calculated similarity scores, as well as the code and computed vectors required to calculate further pairwise similarities. In addition to the raw data, we introduce measures that leverage patent similarity to provide insight into innovation and intellectual property law issues of interest to both scholars and policymakers. Code is provided in accompanying scripts to assist researchers in obtaining the data set, joining it with other available patent data, and using it in their research.

Keywords: Patent, Doc2Vec, Patent Similarity, Patent Distance

JEL Classification: K30, Y10, O34

Suggested Citation: Suggested Citation

Whalen, Ryan and Lungeanu, Alina and DeChurch, Leslie and Contractor, Noshir, Patent Similarity Data and Innovation Metrics (July 21, 2020). Journal of Empirical Legal Studies, 2020, Available at SSRN: https://ssrn.com/abstract=3657462 or http://dx.doi.org/10.2139/ssrn.3657462