Linking innovations and patents - a machine learning assisted method
(2022) In SSRN:s working paper series- 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.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/38d69f07-1c55-42d5-bd95-408a8bd1903e
- author
- Johansson, Mathias LU ; Nyqvist, Jakob LU and Taalbi, Josef LU
- organization
- publishing date
- 2022
- type
- Working paper/Preprint
- publication status
- published
- subject
- keywords
- Innovation, Patents, Machine-learning, LBIO
- in
- SSRN:s working paper series
- pages
- 17 pages
- publisher
- Social Science Research Network (SSRN)
- project
- SWINNO 3.0 Significant Swedish technological Innovations from 1970 until now
- language
- English
- LU publication?
- yes
- id
- 38d69f07-1c55-42d5-bd95-408a8bd1903e
- alternative location
- https://ssrn.com/abstract=4127194
- date added to LUP
- 2022-06-03 18:28:02
- date last changed
- 2023-04-30 12:50:20
@misc{38d69f07-1c55-42d5-bd95-408a8bd1903e, 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.<br/>Data generated using this method can be used to assess many aspects of the relationship between patenting, knowledge accumulation and innovation activity.}}, author = {{Johansson, Mathias and Nyqvist, Jakob and Taalbi, Josef}}, keywords = {{Innovation; Patents; Machine-learning; LBIO}}, language = {{eng}}, note = {{Preprint}}, publisher = {{Social Science Research Network (SSRN)}}, series = {{SSRN:s working paper series}}, title = {{Linking innovations and patents - a machine learning assisted method}}, url = {{https://ssrn.com/abstract=4127194}}, year = {{2022}}, }