2 papers
cs.CL2019
Adversarial Learning of Privacy-Preserving Text Representations for De-Identification of Medical Records
Max Friedrich, Arne Köhn, Gregor Wiedemann +1
De-identification is the task of detecting protected health information (PHI) in medical text. It is a critical step in sanitizing electronic health records (EHRs) to be shared for…
cs.CL2019
Every child should have parents: a taxonomy refinement algorithm based on hyperbolic term embeddings
Rami Aly, Shantanu Acharya, Alexander Ossa +3
We introduce the use of Poincaré embeddings to improve existing state-of-the-art approaches to domain-specific taxonomy induction from text as a signal for both relocating wrong hy…