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nilsdenter / ga_from_semiconductor_patents

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This project contains the data and code used in the paper: Denter, N. M., & Lai, M. Y. (2022). Measuring generative appropriability: Experiments with US semiconductor patents. World Patent Information. doi:10.1016/j.wpi.2022.102130. https://www.sciencedirect.com/science/article/pii/S0172219022000369?dgcid=author

nltk patents patent uspto patent-data patentsview-api patentsview appropriability
  • Updated Aug 21, 2022
  • Python

nilsdenter / novelty_value_ml

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This project contains the data, code and results used in the paper title "On the relationship of novelty and value in digitalization patents: A machine learning approach".

machine-learning scikit-learn machine-learning-algorithms machinelearning patents machine-learning-models partial-dependence-plot machinelearning-python patentsview machine-learning-interpretability permutation-importance kpss machine-learning-interpretation
  • Updated Jul 13, 2022
  • Python

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