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    • CommonLang: a DSL for defining robot tasks 

      Rutle, Adrian; Backer, Jonas; Foldøy, Kolbein; Bye, Robin Trulssen (Journal article; Peer reviewed, 2018)
      Robots are becoming more and more complex and heterogeneous; their abilities and domains of usage are increasing exponentially. Programming these robots requires special skills and usually does not follow standard software ...

    • EVOCROS: Results for OAEI 2019 

      Destro, Juliana Medeiros; Vargas, Javier A; dos Reis, Julio Cesar; Torres, Ricardo Da Silva (Peer reviewed; Journal article, 2019)
      This paper describes the updates in EVOCROS, a crosslingual ontology alignment system suited to create mappings between ontologies described in different natural language. Our tool combines syntactic and semantic similarity ...

    • Ontology changes-driven semantic refinement of cross-language biomedical ontology alignments 

      Destro, Juliana Medeiros; dos Reis, Julio Cesar; Torres, Ricardo Da Silva; Ricarte, Ivan (Peer reviewed; Journal article, 2019)
      Biomedical computational systems benefits from the use of ontologies. However, interconnectivity between these systems is a challenge, specially when the ontologies supporting each system are described in different natural ...

    • Representing Scientific Literature Evolution via Temporal Knowledge Graphs 

      Rossanez, Anderson; Reis, Julio; Torres, Ricardo Da Silva (Peer reviewed; Journal article, 2020)
      Scientific publications register the current knowledge in a specific domain. As new researches are conducted, knowledge evolves, getting documented in dissertations, theses and articles. In this article, we introduce new ...

    • Web-based Scalable Visual Exploration of Large Multidimensional Data Using Human-in-the-Loop Edge Bundling in Parallel Coordinates 

      Cui, Wenqiang; Strazdins, Girts; Wang, Hao (Peer reviewed; Journal article, 2020)
      Visual clutter and overplotting are the main challenges for visualizing large multidimensional data in parallel coordinates, which greatly hampers the recognition of patterns in the data. Although many automatic clustering ...