Now showing items 1-9 of 9

    • Arabic medical entity tagging using distant learning in a multilingual framework 

      Cotik, Viviana; Rodríguez Hontoria, Horacio; Vivaldi, Jorge (Elsevier, 2017-04-30)
      Article
      Open Access
      A semantic tagger aiming to detect relevant entities in Arabic medical documents and tagging them with their appropriate semantic class is presented. The system takes profit of a Multilingual Framework covering four languages ...
    • Combining Wikipedia and WordNet for improving domain terms compilation 

      Vivaldi, Jorge; Rodríguez Hontoria, Horacio; Rigau Claramunt, German (2013)
      External research report
      Open Access
      Domain terms are a useful mean for tuning both resources and NLP processors to domain specific tasks. This paper proposes an improved method for obtaining terms from potentially any domain using the Wikipedia graph structure ...
    • Report on first selection of resources 

      Branco, Antonio; Mendes, Amalia; Trancoso, Isabel; Meinedo, Hugo; Ananiadou, Sophia; Thompson, Paul; McNaught, John; Cristea, Dan; Trandaba¿, Diana; Tufis, Dan; Rosner, Mike; Moreno Bilbao, M. Asunción; Bel, Nùria; Vivaldi, Jorge; Revilla Espí, Eva (2011-03-31)
      External research report
      Open Access
      The central objective of the Metanet4u project is to contribute to the establishment of a pan-European digital platform that makes available language resources and services, encompassing both datasets and software tools, ...
    • Report on methodology and criteria followed for the selection of resources 

      Branco, Antonio; Mendes, Amalia; Trancoso, Isabel; Meinedo, Hugo; Ananiadou, Sophia; Thompson, Paul; McNaught, John; Cristea, Dan; Trandaba¿, Diana; Tufis, Dan; Rosner, Mike; Moreno Bilbao, M. Asunción; Bel, Nùria; Vivaldi, Jorge (2012-11-20)
      External research report
      Open Access
      Deliverable D2.4 del projecte METANET4U (Project CIP #270893)
    • Report on second selection of resources, revising selection in D2.1 

      Branco, Antonio; Mendes, Amalia; Trancoso, Isabel; Meinedo, Hugo; Ananiadou, Sophia; Thompson, Paul; McNaught, John; Cristea, Dan; Trandaba¿, Diana; Tufis, Dan; Rosner, Mike; Moreno Bilbao, M. Asunción; Bel, Nùria; Vivaldi, Jorge (2012-01-31)
      External research report
      Open Access
      The central objective of the Metanet4u project is to contribute to the establishment of a pan-European digital platform that makes available language resources and services, encompassing both datasets and software tools, ...
    • Semantic tagging and normalization of French medical entities 

      Cotik, Viviana; Rodríguez Hontoria, Horacio; Vivaldi, Jorge (CEUR-WS.org, 2016)
      Conference report
      Open Access
      In this paper we present two tools for facing task 2 in CLEF eHealth 2016. The first one is a semantic tagger aiming to detect relevant entities in French medical documents, tagging them with their appropriate ...
    • Semantic tagging of French medical entities using distant learning 

      Cotik, Viviana; Rodríguez Hontoria, Horacio; Vivaldi, Jorge (CEUR-WS.org, 2015)
      Conference lecture
      Open Access
      In this paper we present a semantic tagger aiming to detect relevant entities in French medical documents and tagging them with their appropriate semantic class. These experiments has been carried out in the framework ...
    • Syntactic methods for negation detection in radiology reports in Spanish 

      Cotik, Viviana; Stricker, Vanesa; Vivaldi, Jorge; Rodríguez Hontoria, Horacio (Association for Computational Linguistics, 2016)
      Conference report
      Open Access
      Identification of the certainty of events is an important text mining problem. In particular, biomedical texts report medical conditions or findings that might be factual, hedged or negated. Identification ...
    • Using Wikipedia for domain terms extraction 

      Vivaldi, Jorge; Rodríguez Hontoria, Horacio (2012)
      Conference report
      Restricted access - publisher's policy
      Domain terms are a useful resource for tuning both resources and NLP processors to domain specific tasks. This paper proposes a method for obtaining terms from potentially any domain using Wikipedia.