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GTM2017_extended_abstract_32.pdf
Preview of https://vpinstitute. org/wp-content/uploa ds/2017/10/GTM2017_e xtended_abstract_32. pdf
🔗 Source: vpinstitute.org
📊 Size: 107 KB
👤 Author: Arho Suominen
⬇️ Downloads: 63

Summary

Studies have used various approaches to measure knowledge flows between scholarly literature and patents, including keyword search, patent citations, and author-inventor co-occurrences. This study analyzes the relationship between publications and patents by comparing human-assigned and machine-learned linkages between science and patents. A machine learning approach using Latent Dirichlet Allocation (LDA) was applied to a dataset of Finnish publications and patents, resulting in 150 topics. The topic distribution of both patents and publications was found to be near equally unconcentrated, with patents focusing on telecommunication and electronics, and publications focusing on social sciences, management, and medical research. The study also analyzed non-patent citations, finding that patents and publications have different thematic focuses, with some topics showing significant disparity in patent or publication difference.

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Studies have used various approaches to measure knowledge flows between scholarly literature and patents, including keyword search, patent citations, and...

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  • File Format: PDF
  • File Size: 107 KB
  • Pages: 3
  • Language: EN
  • Author: Arho Suominen
  • Total Downloads: 63
  • Last Updated: 10 hours ago

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