Now showing items 1-3 of 3

    • Drug target discovery using knowledge graph embeddings 

      Mohamed, Sameh K.; Nováček, Vít; Nounu, Aayah (Association for Computing Machinery, 2019-04-08)
      The field of drug discovery has entered a plateau stage lately. It is increasingly more expensive and time-demanding to introduce new drugs into the market. One of the main reasons is the slow progress in finding novel ...
    • Link prediction using multi part embeddings 

      Mohamed, Sameh K.; Nováček, Vít (NUI Galway, 2019-06-02)
      Knowledge graph embeddings models are widely used to provide scalable and efficient link prediction for knowledge graphs. They use different techniques to model embeddings interactions, where their tensor factorisation ...
    • Uncovering semantic bias in neural network models using a knowledge graph 

      Nikolov, Andriy; d'Aquin, Mathieu (ACM, 2020-10-19)
      While neural networks models have shown impressive performance in many NLP tasks, lack of interpretability is often seen as a disadvantage. Individual relevance scores assigned by post-hoc explanation methods are not ...