• An evaluation of recommendation algorithms for online recipe portals 

      Trattner, Christoph; Elsweiler, David (Peer reviewed; Journal article, 2019)
      Better models of food preferences are required to realise the oft touted potential of food recommenders to aid with the obesity crisis. Many of the food recommender evaluations in the literature have been performed with ...
    • Recommender systems in the healthcare domain: state-of-the-art and research issues 

      Tran, Thi NgocTrang; Felfernig, Alexander; Trattner, Christoph; Holzinger, Andreas (Journal article; Peer reviewed, 2020)
      Nowadays, a vast amount of clinical data scattered across different sites on the Internet hinders users from finding helpful information for their well-being improvement. Besides, the overload of medical information (e.g., ...
    • Towards a Big Data Platform for News Angles 

      Gallofré Ocaña, Marc; Nyre, Lars; Opdahl, Andreas Lothe; Tessem, Bjørnar; Trattner, Christoph; Veres, Csaba (Conference object; Peer reviewed; Journal article, 2019)
      Finding good angles on news events is a central journalistic and editorial skill. As news work becomes increasingly computer-assisted and big-data based, journalistic tools therefore need to become better able to support ...
    • Towards Responsible Media Recommendation 

      Elahi, Mehdi; Jannach, Dietmar; Skjærven, Lars; Knudsen, Erik; Sjøvaag, Helle; Tolonen, Kristian; Holmstad, Øyvind; Pipkin, Igor; Throndsen, Eivind; Stenbom, Agnes; Fiskerud, Eivind; Oesch, Adrian; Vredenberg, Loek; Trattner, Christoph (Journal article; Peer reviewed, 2021)
      Reading or viewing recommendations are a common feature on modern media sites. What is shown to consumers as recommendations is nowadays often automatically determined by AI algorithms, typically with the goal of helping ...
    • Visual cultural biases in food classification 

      Zhang, Qing; Elsweiler, David; Trattner, Christoph (Journal article; Peer reviewed, 2020)
      This article investigates how visual biases influence the choices made by people and machines in the context of online food. To this end the paper investigates three research questions and shows (i) to what extent machines ...
    • What online data say about eating habits 

      Trattner, Christoph; Elsweiler, David (Peer reviewed; Journal article, 2019)
      Understanding how individuals shift to diets with much smaller ecological footprints may help us in persuading more people to change their habits and transition to more sustainable food systems. Online interactions provide ...