Now showing items 1-8 of 8

    • 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 ...
    • 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 ...
    • On learnability of constraints from RDF data 

      Muñoz, Emir (Springer International Publishing, 2016-05-14)
      RDF is structured, dynamic, and schemaless data, which enables a big deal of flexibility for Linked Data to be available in an open environment such as the Web. However, for RDF data, flexibility turns out to be the source ...
    • 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 ...
    • Using linked data to mine RDF from wikipedia's tables 

      Muñoz, Emir; Hogan, Aidan; Mileo, Alessandra (ACM, 2014)
      The tables embedded in Wikipedia articles contain rich, semi-structured encyclopaedic content. However, the cumulative content of these tables cannot be queried against. We thus propose methods to recover the semantics of ...
    • Validation of expressive XML keys with XML schema and XQuery 

      Liu, Bo; Link, Sebastian; Muñoz, Emir (ACS, 2015)
      The eXtensible Markup Language (XML) is the defacto industry standard for exchanging data on the Web and elsewhere. While the relational model of data enjoys a well-accepted definition of a key, several competing notions ...