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Browsing Department of Information Science and Media Studies by Subject "hybrid recommender systems"

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    • Video Recommendations Based on Visual Features Extracted with Deep Learning 

      Kvifte, Tord (Master thesis, 2021-06-01)
      When a movie is uploaded to a movie Recommender System (e.g., YouTube), the system can exploit various forms of descriptive features (e.g., tags and genre) in order to generate personalized recommendation for users. However, ...

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