Reader centric real-time electric magazine article generator

  title={Reader centric real-time electric magazine article generator},
  author={Tomoki Takada and Yuri Taira and Shinya Akatsuka and Mizuki Arai and Tomohiro Takagi and Nobuhito Maruyama},
  journal={2011 IEEE International Conference on Systems, Man, and Cybernetics},
A real-time E-magazine article generation system that uses two article recommendation systems have been developed. The first recommendation system is called the Relevance-Based Recommender, which uses mutual information, and the second is called the Reading History Based Recommender, which uses a confabulation model. Both systems were found to recommend suitable articles.