Using the contextual language model BERT for multi-criteria classification of scientific articles.

Journal: Journal of biomedical informatics
Published Date:

Abstract

BACKGROUND: Finding specific scientific articles in a large collection is an important natural language processing challenge in the biomedical domain. Systematic reviews and interactive article search are the type of downstream applications that benefit from addressing this problem. The task often involves screening articles for a combination of selection criteria. While machine learning was previously used for this purpose, it is not known if different criteria should be modeled together or separately in an ensemble model. The performance impact of the modern contextual language models on the task is also not known.

Authors

  • Ashwin Karthik Ambalavanan
    Arizona State University, United States.
  • Murthy V Devarakonda
    IBM Research, USA. Electronic address: mvd@acm.org.