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 ...
    • Linking knowledge graphs across languages with semantic similarity and machine translation 

      McCrae, John P.; Arcan, Mihael; Buitelaar, Paul (MLP 2017, 2017-09-04)
      Knowledge graphs and ontologies underpin many natural language processing applications, and to apply these to new languages, these knowledge graphs must be translated. Up until now, this has been achieved either by direct ...
    • Measuring accuracy of triples in knowledge graphs 

      Liu, Shuangyan; d’Aquin, Mathieu; Motta, Enrico (Springer, 2017-06-19)
      An increasing amount of large-scale knowledge graphs have been constructed in recent years. Those graphs are often created from text-based extraction, which could be very noisy. So far, cleaning knowledge graphs are ...
    • Mining cardinalities from knowledge bases 

      Muñoz, Emir; Nickles, Matthias (Springer Verlag, 2017-08-01)
      Cardinality is an important structural aspect of data that has not received enough attention in the context of RDF knowledge bases (KBs). Information about cardinalities can be useful for data users and knowledge engineers ...
    • 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 ...