Personalized Recommendation via Parameter-Free Contextual Bandits

  title={Personalized Recommendation via Parameter-Free Contextual Bandits},
  author={Liang Tang and Yexi Jiang and Lei Li and Chunqiu Zeng and Tao Li},
Personalized recommendation services have gained increasing popularity and attention in recent years as most useful information can be accessed online in real-time. Most online recommender systems try to address the information needs of users by virtue of both user and content information. Despite extensive recent advances, the problem of personalized recommendation remains challenging for at least two reasons. First, the user and item repositories undergo frequent changes, which makes… CONTINUE READING
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Online bagging and boosting

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