Published on in Vol 22, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18055, first published .
Exploring the Privacy-Preserving Properties of Word Embeddings: Algorithmic Validation Study

Exploring the Privacy-Preserving Properties of Word Embeddings: Algorithmic Validation Study

Exploring the Privacy-Preserving Properties of Word Embeddings: Algorithmic Validation Study

Mohamed Abdalla 1, 2, 3, BSc, MSc;  Moustafa Abdalla 4, 5, 6, BSc, DPhil;  Graeme Hirst 1, 3, BSc, PhD;  Frank Rudzicz 1, 3, 7, 8, BSc, MSc, PhD

1 Department of Computer Science, University of Toronto , Toronto, ON, CA

2 Institute for Clinical Evaluative Sciences , Toronto, ON, CA

3 The Vector Institute for Artificial Intelligence , Toronto, ON, CA

4 Deptartment of Statistics, Computational Statistics & Machine Learning Group, University of Oxford, Oxford , GB

5 Wellcome Centre for Human Genetics, Nuffield Dept of Medicine, University of Oxford, Oxford , GB

6 Harvard Medical School , Boston, MA, US

7 International Centre for Surgical Safety, Li Ka Shing Knowledge Institute, St Michael’s Hospital, Toronto, ON, CA

8 Surgical Safety Technologies Inc , Toronto, ON, CA

Corresponding Author:

  • Mohamed Abdalla, BSc, MSc
  • Department of Computer Science
  • University of Toronto
  • Bahen Centre for Information Technology
  • 40 St. George Street, Room 4283
  • Toronto, ON
  • CA
  • Phone: 1 4169787816
  • Email: mohamed.abdalla@mail.utoronto.ca