Business School events
Browse events involving the University of Sussex Business School.
Tracing the Flow of Knowledge From Science to Technology Using Deep Learning
To register for this seminar with Eventbrite please click here
Abstract:
We identify a similarity model suitable for working with patents and scientific publications at the same time. In a horse race-style evaluation, we subject eight language (similarity) models to prediction credible Patent-Paper Citations. We find that our Pat-SPECTER model performs best, which the SPECTER2 model fine-tuned on patents. In two real-world scenarios (separating patent-paper-pairs and predicting patent-paper-pairs) we demonstrate the capabilities of the Pat-SPECTER. Using the model, we finally study which patent characteristics (authorities, CPC classes) predict references to related scientific literature. The model is open for the academic community and practitioners alike.
Bio:
Michael E. Rose is a senior research fellow at the Max Planck Institute for Innovation and Competition. He holds a PhD in Economics from the University of Cape Town. His research interests include Economics of Science, Technology Transfer (both in historic and contemporaneous perspective), and Digital Transformation.
Link: https://michael-e-rose.github.io/