Projects per year
Abstract
This paper describes the methodology behind the matching of patents and a literature-based innovation output indicator (LBIO) collected from trade journals covering the manufacturing and ICT service sectors in Sweden 1970-2015. A combination of manual processing and simple machine learning tools has enabled the identification, classification and linking of patents that otherwise would have been very difficult for either of the methods to detect on its own.
Data generated using this method can be used to assess many aspects of the relationship between patenting, knowledge accumulation and innovation activity.
Data generated using this method can be used to assess many aspects of the relationship between patenting, knowledge accumulation and innovation activity.
| Original language | English |
|---|---|
| Publisher | Social Science Research Network (SSRN) |
| Number of pages | 17 |
| Publication status | Published - 2022 |
Publication series
| Name | SSRN:s working paper series |
|---|---|
| Publisher | Social Science Research Network (SSRN) |
Subject classification (UKÄ)
- Social Sciences Interdisciplinary
Free keywords
- Innovation
- Patents
- Machine-learning
- LBIO
Fingerprint
Dive into the research topics of 'Linking innovations and patents - a machine learning assisted method'. Together they form a unique fingerprint.Projects
- 1 Active
-
SWINNO 3.0 Significant Swedish technological Innovations from 1970 until now
Taalbi, J. (PI), Chaminade, C. (Researcher), Fink, J. (Researcher), Hylmö, A. (Researcher), Kander, A. (Researcher), Kreutzer, P. J. (Researcher), Torregrosa Hetland, S. (Researcher), van der Most, F. (Research engineer), Kilicaslan, A. (Research assistant), Krumova, R. (Research assistant) & Nyqvist, J. (Research assistant)
Swedish Government Agency for Innovation Systems (Vinnova)
2020/03/06 → 2025/01/30
Project: Research