Now showing items 1-5 of 5

    • Identifying equivalent relation paths in knowledge graphs 

      Mohamed, Sameh K.; Muñoz, Emir; Nováček, Vít; Vandenbussche, Pierre-Yves (Springer Verlag, 2017-06-19)
      Relation paths are sequences of relations with inverse that allow for complete exploration of knowledge graphs in a two-way unconstrained manner. They are powerful enough to encode complex relationships between entities ...
    • Knowledge base completion using distinct subgraph paths 

      Mohamed, Sameh K.; Nováček, Vít; Vandenbussche, Pierre-Yves (ACM, 2018-04-09)
      Graph feature models facilitate efficient and interpretable predictions of missing links in knowledge bases with network structure (i.e. knowledge graphs). However, existing graph feature models-e.g. Subgraph Feature ...
    • Regularizing knowledge graph embeddings via equivalence and inversion axioms 

      Minervini, Pasquale; Costabello, Luca; Muñoz, Emir; Nováček, Vít; Vandenbussche, Pierre-Yves (Springer Verlag, 2017-12-30)
      Learning embeddings of entities and relations using neural architectures is an effective method of performing statistical learning on large-scale relational data, such as knowledge graphs. In this paper, we consider the ...
    • SemanTex: semantic text exploration using document links implied by conceptual networks extracted from the texts 

      Aldarra, Suad; Muñoz, Emir; Vandenbussche, Pierre-Yves; Nováček, Vít (ACMCEUR-WS.org, 2014)
      Despite of advances in digital document processing, exploration of implicit relationships within large amounts of textual resources can still be daunting. This is partly due to the ‘black-box’ nature of most current ...
    • Using drug similarities for discovery of possible adverse reactions 

      Muñoz, Emir; Nováček, Vít; Vandenbussche, Pierre-Yves (AMIA, 2017-02-10)
      We propose a new computational method for discovery of possible adverse drug reactions. The method consists of two key steps. First we use openly available resources to semi-automatically compile a consolidated data set ...