Combining lexical and context features for automatic ontology extension.

Journal: Journal of biomedical semantics
Published Date: Jan 13, 2020

Abstract

BACKGROUND: Ontologies are widely used across biology and biomedicine for the annotation of databases. Ontology development is often a manual, time-consuming, and expensive process. Automatic or semi-automatic identification of classes that can be added to an ontology can make ontology development more efficient.

Authors

  • Sara Althubaiti
    Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.
  • Şenay Kafkas
    European Molecular Biology Laboratory (EMBL-EBI), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, UK. kafkas@ebi.ac.uk.
  • Marwa Abdelhakim
    Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.
  • Robert Hoehndorf
    Computational Bioscience Research Center, King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Saudi Arabia. robert.hoehndorf@kaust.edu.sa.

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