Workshop on Recommendation Systems for Television and Online Video

For many households the television is still the central entertainment hub in their home, and the average TV viewer spends about half of their leisure time in front of a TV (3-5 hours/day). The choice of what to watch becomes more overwhelming though because the entertainment options are scattered across various channels, such as on-demand video, digital recorders and the traditional linear TV. Recommendation systems provide TV users with suggestions about both online video-on-demand and broadcast content and help them to search and browse intelligently for content that is relevant to them.

While many open questions in video-on-demand recommendations have already been solved, recommendation systems for broadcast content (e.g., linear channels and catch-up TV) still experience a number of unique challenges due to the peculiarity of such domain. The RecSysTV 2016 workshop aims to provide a dedicated venue for papers covering all aspects of this recommendation problem.

  • Jan Neumann, Comcast Labs, USA
  • John Hannon, Zalando, Ireland
  • Claudio Riefolo, ContentWise, Italy
  • Hassan Sayyadi, Comcast Labs, USA


Thursday, Sept 15, 2016, 09:00-17:30


IBM (Aud A)

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