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, 2 , BSc, PhD ;   Frank Rudzicz   1, 2, 7, 8 , BSc, MSc, PhD

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

2 The Vector Institute for Artificial Intelligence, Toronto, ON, Canada

3 Institute for Clinical Evaluative Sciences, Toronto, ON, Canada

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

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

6 Harvard Medical School, Boston, MA, United States

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

8 Surgical Safety Technologies Inc, Toronto, ON, Canada

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, M5S 2E4
  • Canada
  • Phone: 1 4169787816
  • Email: mohamed.abdalla@mail.utoronto.ca