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Group Recommender Systems

Contributions focusing on different new and relevant aspects of group recommender systems, in particular, new developments on the algorithmic and user interface level as well as new applications, all accompanied by a corresponding evaluation (e.g., empirical study) that clearly shows significant improvements compared to the state of the art.

Participating journal

User Modeling and User-Adapted Interaction provides an interdisciplinary forum for the dissemination of novel and significant original research results about interactive computer...

Editors

  • Ludovico Boratto

    Ludovico Boratto

    Associate Professor of Computer Science at the University of Cagliari, Cagliari (Italy). I am a research scientist with a background on Information Retrieval. Most of my research involves discovering patterns in user behavior, to provide useful information to the users. I have worked on recommender systems, clustering algorithms, social media analysis, and natural language processing. My current research interests focus on algorithmic bias on the Web, to generate fair and non-discriminating rankings.
  • Alexander Felfernig

    Alexander Felfernig

    Alexander Felfernig is a full professor at the Graz University of Technology (Austria) since March 2009. He received his PhD in Computer Science from the University of Klagenfurt. Alexander directs the Applied Software Engineering & Artificial Intelligence research group (ASE). His research interests include configuration systems, recommender systems, sustainability aspects, model-based diagnosis, software requirements engineering, different aspects of human decision making, and knowledge acquisition methods.
  • Martin Stettinger

    Martin Stettinger

    Graz University of Technology (Austria)
  • Marko Tkalčič

    Marko Tkalčič

    Associate professor at the Faculty of Mathematics, Natural Sciences and Information Technologies (FAMNIT) at the University of Primorska in Koper, Slovenia. I aim at improving personalized services (e.g. recommender systems) through the usage of psychological models in personalization algorithms. To achieve this, I use diverse research methodologies, including data mining, machine learning, and user studies.

Articles

Showing 1-6 of 6 articles

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