Browsing Research Institutes and Centres by Subject "Machine learning"

Now showing items 1-5 of 5

    • Composite measures for assessing multidimensional social exclusion in later life: Conceptual and methodological challenges 

      Keogh, Sinéad; O’Neill, Stephen; Walsh, Kieran (Springer, 2021-01-25)
      Although there are a number of approaches to constructing a measure of multidimensional social exclusion in later life, theoretical and methodological challenges exist around the aggregation and weighting of constituent ...

    • A hybrid method for rating prediction using linked data features and text reviews 

      Yumusak, Semih; Muñoz, Emir; Minervini, Pasquale; Dogdu, Erdogan; Kodaz, Halife (CEUR-WS.org, 2016)
      This paper describes our entry for the Linked Data Mining Challenge 2016, which poses the problem of classifying music albums as good or bad by mining Linked Data. The original labels are assigned according to aggregated ...

    • In or out? Real-time monitoring of BREXIT sentiment on Twitter 

      Vasiliu, Laurentiu; Freitas, André; Caroli, Frederico; McDermott, Ross; Zarrouk, Manel; Hürlimann, Manuela; Davis, Brian; Daudert, Tobias; Khaled, Malek Ben; Byrne, David; Fernández, Sergio; Cavallini, Angelo (CEUR Workshop Proceedings, 2016-09-12)
      The SSIX (Social Sentiment analysis financial IndeXes) project is a European Innovation Project sponsored by the European Commission under the Horizon 2020 framework. SSIX aims to provide European SMEs with a collection ...

    • Multiclass SVM for bladder volume monitoring using electrical impedance measurements 

      Santorelli, Adam; Dunne, Eoghan; Porter, Emily; O'Halloran, Martin (IEEE, 2018-11-08)
      Urinary incontinence is a common condition that impacts the quality of life from those who suffer from it. Electrical impedance measurements offer the potential for a non-invasive low-cost solution to monitor changes in ...

    • 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 ...