Projekt per år
Sammanfattning
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.
| Originalspråk | engelska |
|---|---|
| Utgivare | Social Science Research Network (SSRN) |
| Antal sidor | 17 |
| Status | Published - 2022 |
Publikationsserier
| Namn | SSRN:s working paper series |
|---|---|
| Förlag | Social Science Research Network (SSRN) |
Ämnesklassifikation (UKÄ)
- Tvärvetenskapliga studier
Fingeravtryck
Utforska forskningsämnen för ”Linking innovations and patents - a machine learning assisted method”. Tillsammans bildar de ett unikt fingeravtryck.Projekt
- 1 Avslutade
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SWINNO 3.0 Significant Swedish technological Innovations from 1970 until now
Taalbi, J. (PI), Chaminade, C. (Forskare), Fink, J. (Forskare), Hylmö, A. (Forskare), Kander, A. (Forskare), Kreutzer, P. J. (Forskare), Torregrosa Hetland, S. (Forskare), van der Most, F. (Forskningsingenjör), Kilicaslan, A. (Forskningsassistent), Krumova, R. (Forskningsassistent) & Nyqvist, J. (Forskningsassistent)
Swedish Government Agency for Innovation Systems (Vinnova)
2020/03/06 → 2025/01/30
Projekt: Forskning