Collection

Group Recommender Systems

Submission status
Closed
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.

Editors

  • Ludovico Boratto Ludovico Boratto , 

    Ludovico Boratto

    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

    Full professor at the Graz University of Technology (Austria) since March 2009. I direct the Applied Software Engineering & Artificial Intelligence research group (ASE). My research interests include configuration systems, recommender systems, model-based diagnosis, software requirements engineering, different aspects of human decision making, and knowledge acquisition methods.

  • Martin Stettinger Martin Stettinger  &

    Martin Stettinger

    Graz University of Technology (Austria)

  • Marko Tkalčič 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 (6 in this collection)