Patent-publication pairs for the detection of knowledge transfer from research to industry: reducing ambiguities with word embeddings and references

TL;DR

This paper presents a method to identify publication-patent pairs in medical research by using name matching, text similarity with word embeddings, and reference analysis to assess knowledge transfer from research to industry.

Contribution

It introduces a novel pipeline combining name matching, text similarity via word embeddings, and reference analysis to accurately identify research-to-industry knowledge transfer.

Findings

Effective identification of publication-patent pairs over five years

Use of word embeddings improves text similarity assessment

Validated patent classes for medical research domain

Abstract

The performance of medical research can be viewed and evaluated not only from the perspective of publication output, but also from the perspective of economic exploitability. Patents can represent the exploitation of research results and thus the transfer of knowledge from research to industry. In this study, we set out to identify publication-patent pairs in order to use patents as a proxy for the economic impact of research. To identify these pairs, we matched scholarly publications and patents by comparing the names of authors and investors. To resolve the ambiguities that arise in this name-matching process, we expanded our approach with two additional filter features, one used to assess the similarity of text content, the other to identify common references in the two document types. To evaluate text similarity, we extracted and transformed technical terms from a medical ontology (MeSH) into numerical vectors using word embeddings. We then calculated the results of the two supporting features over an example five-year period. Furthermore, we developed a statistical procedure which can be used to determine valid patent classes for the domain of medicine. Our complete data processing pipeline is freely available, from the raw data of the two document types right through to the validated publication-patent pairs.