Journal article

Adaptive model for recommendation of news

  • Medo, Matúš Physics Department, University of Fribourg, Switzerland
  • Zhang, Yi-Cheng Physics Department, University of Fribourg, Switzerland
  • Zhou, Tao Physics Department, University of Fribourg, Switzerland - Department of Modern Physics, University of Science and Technology of China - Hefei, PRC
Published in:
  • Europhysics Letters. - 2009, vol. 88, no. 3, p. 38005
English Most news recommender systems try to identify users' interests and news' attributes and use them to obtain recommendations. Here we propose an adaptive model which combines similarities in users' rating patterns with epidemic-like spreading of news on an evolving network. We study the model by computer agent-based simulations, measure its performance and discuss its robustness against bias and malicious behavior. Subject to the approval fraction of news recommended, the proposed model outperforms the widely adopted recommendation of news according to their absolute or relative popularity. This model provides a general social mechanism for recommender systems and may find its applications also in other types of recommendation.
Faculté des sciences et de médecine
Département de Physique
  • English
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