Blar i Department of Information Science and Media Studies på forfatter "Trattner, Christoph"

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    • Boosting Health? Examining the Role of Nutrition Labels and Preference Elicitation Methods in Food Recommendation 

      Starke, Alain Dominique; el Majjodi, Ayoub; Trattner, Christoph (Chapter, 2022)
      How users evaluate a recommender system goes beyond the accuracy of the presented content. For food recommendation, users differ in terms of the needs they have. We investigated whether users with different levels of health ...

    • Changing Salty Food Preferences with Visual and Textual Explanations in a Search Interface 

      Berge, Arngeir; Sjøen, Vegard Velle; Starke, Alain; Trattner, Christoph (Journal article; Peer reviewed, 2021)
      Salt is consumed at too high levels in the general population, causing high blood pressure and related health problems. In this paper, we present results of ongoing research that tries to reduce salt intake via technology ...

    • The Cholesterol Factor: Balancing Accuracy and Health in Recipe Recommendation Through a Nutrient-Specific Metric 

      Starke, Alain Dominique; Trattner, Christoph; Bakken, Hedda; Johannessen, Martin Skivenesvåg; Solberg, Vegard (Chapter, 2021)
      Whereas many food recommender systems optimize for users’ preferences, health is another but often overlooked objective. This paper aims to recommend relevant recipes that avoid nutrients that contribute to high levels of ...

    • Considering temporal aspects in recommender systems: a survey 

      Bogina, Veronika; Kuflik, Tsvi; Jannach, Dietmar; Bielikova, Maria; Kompan, Michal; Trattner, Christoph (Journal article; Peer reviewed, 2022)
      The widespread use of temporal aspects in user modeling indicates their importance, and their consideration showed to be highly effective in various domains related to user modeling, especially in recommender systems. ...

    • A day at the races: Using best arm identification algorithms to reduce the cost of information retrieval user studies 

      Losada, David E.; Elsweiler, David; Harvey, Morgan; Trattner, Christoph (Journal article; Peer reviewed, 2021)
      Two major barriers to conducting user studies are the costs involved in recruiting participants and researcher time in performing studies. Typical solutions are to study convenience samples or design studies that can be ...

    • Designing for Control in Nurse-AI Collaboration During Emergency Medical Calls 

      Berge, Arngeir; Guribye, Frode; Fotland, Siri-Linn Schmidt; Fonnes, Gro; Johansen, Ingrid H.; Trattner, Christoph (Chapter, 2023)
      AI-powered symptom checkers are automating the work of telephone triage nurses in assessing patient urgency. Yet, these systems exclude several vulnerable patient groups and overlook telenurses’ competent interaction with ...

    • Developing and Evaluating a University Recommender System 

      Elahi, Mehdi; Starke, Alain Dominique; El Ioini, Nabil; Lambrix, Anna Alexander; Trattner, Christoph (Journal article; Peer reviewed, 2022)
      A challenge for many young adults is to find the right institution to follow higher education. Global university rankings are a commonly used, but inefficient tool, for they do not consider a person's preferences and needs. ...

    • 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 ...

    • Healthiness and environmental impact of dinner recipes vary widely across developed countries 

      Angelsen, Aslaug Linnea; Starke, Alain Dominique; Trattner, Christoph (Journal article; Peer reviewed, 2023)
      Contrary to food ingredients, little is known about recipes’ healthiness or environmental impact. Here we examine 600 dinner recipes from Norway, the UK and the USA retrieved from cookbooks and the Internet. Recipe healthiness ...

    • The Interplay between Food Knowledge, Nudges, and Preference Elicitation Methods Determines the Evaluation of a Recipe Recommender System 

      el Majjodi, Ayoub; Starke, Alain Dominique; Elahi, Mehdi; Trattner, Christoph (Chapter, 2023)
      Domain knowledge can affect how a user evaluates different aspects of a recommender system. Recipe recommendations might be difficult to understand, as some health aspects are implicit. The appropri- ateness of a recommender’s ...

    • Nudging Healthy Choices in Food Search Through Visual Attractiveness 

      Starke, Alain D.; Willemsen, Martijn C.; Trattner, Christoph (Journal article; Peer reviewed, 2021)
      Recipe websites are becoming increasingly popular to support people in their home cooking. However, most of these websites prioritize popular recipes, which tend to be unhealthy. Drawing upon research on visual biases and ...

    • Nudging Towards Health? Examining the Merits of Nutrition Labels and Personalization in a Recipe Recommender System 

      el Majjodi, Ayoub; Starke, Alain Dominique; Trattner, Christoph (Chapter, 2022)
      Food recommender systems show personalized recipes to users based on content liked previously. Despite their potential, often recommended (popular) recipes in previous studies have turned out to be unhealthy, negatively ...

    • 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., ...

    • Responsible media technology and AI: challenges and research directions 

      Trattner, Christoph; Jannach, Dietmar; Motta, Enrico; Meijer, Irene Costera; Diakopoulos, Nicholas; Elahi, Mehdi; Opdahl, Andreas Lothe; Tessem, Bjørnar; Borch, Njål Trygve; Fjeld, Morten; Øvrelid, Lilja; De Smedt, Koenraad; Moe, Hallvard (Journal article; Peer reviewed, 2021)
      The last two decades have witnessed major disruptions to the traditional media industry as a result of technological breakthroughs. New opportunities and challenges continue to arise, most recently as a result of the rapid ...

    • “Tell Me Why”: using natural language justifications in a recipe recommender system to support healthier food choices 

      Starke, Alain Dominique; Musto, Cataldo; Rapp, Amon; Semeraro, Giovanni; Trattner, Christoph (Journal article; Peer reviewed, 2023)
      Users of online recipe websites tend to prefer unhealthy foods. Their popularity under- mines the healthiness of traditional food recommender systems, as many users lack nutritional knowledge to make informed food decisions. ...

    • Topical Preference Trumps Other Features in News Recommendation: A Conjoint Analysis on a Representative Sample from Norway 

      Knudsen, Erik; Starke, Alain Dominique; Trattner, Christoph (Journal article; Peer reviewed, 2023)
      A variety of news articles features can be used to tailor news content. However, only a few studies have actually compared the relative importance of different features in predicting news reading behavior in the context ...

    • Towards a Big Data Platform for News Angles 

      Gallofré Ocaña, Marc; Nyre, Lars; Opdahl, Andreas Lothe; Tessem, Bjørnar; Trattner, Christoph; Veres, Csaba (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 Attitudinal Change in News Recommender Systems: A Pilot Study on Climate Change 

      Jeng, Jia-Hua; Starke, Alain Dominique; Trattner, Christoph (Chapter, 2023)

    • 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 ...

    • Trustworthy journalism through AI 

      Opdahl, Andreas Lothe; Tessem, Bjørnar; Dang Nguyen, Duc Tien; Motta, Enrico; Setty, Vinay; Throndsen, Eivind; Tverberg, Are; Trattner, Christoph (Journal article; Peer reviewed, 2023)
      Quality journalism has become more important than ever due to the need for quality and trustworthy media outlets that can provide accurate information to the public and help to address and counterbalance the wide and rapid ...