Biomedical word sense disambiguation with bidirectional long short-term memory and attention-based neural networks.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: In recent years, deep learning methods have been applied to many natural language processing tasks to achieve state-of-the-art performance. However, in the biomedical domain, they have not out-performed supervised word sense disambiguation (WSD) methods based on support vector machines or random forests, possibly due to inherent similarities of medical word senses.

Authors

  • Canlin Zhang
    Department of Mathematics, Florida State University, Tallahassee, FL, US.
  • Daniel Biś
    Department of Computer Science, Florida State University, Tallahassee, FL, US.
  • Xiuwen Liu
    Department of Computer Science, Florida State University, Tallahassee, FL 32306-4530, United States. Electronic address: liux@cs.fsu.edu.
  • Zhe He
    School of Information, Florida State University, Tallahassee, FL, USA.