Now showing items 1-5 of 744

    • Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities 

      Chen, J; Dong, H; Hastings, J; et al. (Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 19 December 2023)
      The term life sciences refers to the disciplines that study living organisms and life processes, and include chemistry, biology, medicine, and a range of other related disciplines. Research efforts in life sciences are ...
    • DeepOnto: A Python package for ontology engineering with deep learning 

      He, Y; Chen, J; Dong, H; et al. (IOS Press, 2024)
      Integrating deep learning techniques, particularly language models (LMs), with knowledge representation techniques like ontologies has raised widespread attention, urging the need of a platform that supports both paradigms. ...
    • Taxonomy completion via implicit concept insertion 

      Shi, J; Dong, H; Chen, J; et al. (Association for Computing Machinery, 2024)
      High quality taxonomies play a critical role in various domains such as e-commerce, web search and ontology engineering. While there has been extensive work on expanding taxonomies from externally mined data, there has ...
    • A Language Model based Framework for New Concept Placement in Ontologies 

      Dong, H; Chen, J; He, Y; et al. (Springer, 2024)
      We investigate the task of inserting new concepts extracted from texts into an ontology using language models. We explore an ap proach with three steps: edge search which is to find a set of candidate locations to insert ...
    • Exploring the Uncertainty of Approximated Fitness Landscapes via Gaussian Process Realisations 

      Karatas, MD; Goodfellow, M; Fieldsend, JE (Institute of Electrical and Electronics Engineers (IEEE), 1 January 2024)
      Gaussian processes (GPs) serve as powerful surrogate models in optimisation by providing a flexible data-driven framework for representing complex fitness landscapes. We provide an analysis of realisations drawn from GP ...