RecSysTV Program – 10th October 2014, Foster City, Silicon Valley, USA
Morning Session
- 9:00-9:15 Welcome & Introductions
- 9:15-:10:00 (Invited Talk) Addressable Ad Targeting for TV, B. Kitts (Adap.tv)
- 10:00-10:30 (Invited Talk) Personalized Page Generation for Browsing Recommendations, J. Basilico (Netflix)
- 10:30-11:00 Morning Break
Mid-Morning Session
Lunch Demo/Poster Sessions
- 11:45-12:15 Comcast, Boxfish, GraphLab Presentations
- 12:15-14:00 Lunch with Posters & Demonstrations from Attendees
Posters
- R. Turrin – Time-based TV Programs Prediction
- H. Corona – A Mood-based Genre Classification of Television Content
- J. Kuchař – Bag-of-Entities Text Representation for Client-side TV Recommender Systems
- K. Yamamoto – Content-based Viewer Estimation Using Image Features for Recommendation of Video Clips
- A. Taşci – A Graph-based Collaborative and Context-aware Recommendation System for TV Programs
- M. Sharma – Feature-based Bilinear Similarity Model for Top-n Recommendation of New Items
Demos
- J. Neumann – Comcast
- J. Hannon – Boxfish
- D. Bickson – GraphLab
- B. Kitts – Adap.tv
- D. Zibriczky – ImpressTV
- P. Auteri – Contentwise
- J. Delgado – OnCue TV
Afternoon Session
- 14:00-14:45 (Invited Talk) Building Large-Scale Recommender Systems for TV, J. Hu (Samsung)
- 14:45-15:00 Item-Based Collaborative Filtering Using the Big Five Personality Traits, H. Alharthi et al.
- 15:00-15:15 The Cold Start: Minimal User’s Rating Activity Estimation, O. Kaššák et al.
- 15:15-15:30 A Mood-based Genre Classification of Television Content, H. Corona Pampín et al.
- 15:30-16:00 Afternoon Break
Mid-Afternoon Session
- 16:00-16:15 Bag-of-Entities text representation for client-side TV recommender systems, J. Kuchař et al.
- 16:15-16:30 Content-based Viewer Estimation Using Image Features for Recommendation of Video Clips, K. Yamamoto et al.
- 16:30-16:45 Pilot User Selection Method for Joint-Prediction of Ratings and Popularity on Cold-Start Item, Z. Miao et al.
- 16:45-17:00 Wrap Up and Awards
Organizing committee
Danny Bickson, Graphlab Inc., Seattle, WA
John Hannon, Boxfish, Palo Alto, CA
Jan Neumann, Comcast Labs, Washington, DC
Hassan Sayyadi, Comcast Labs, Washington, DC
Program committee:
Justin Basilico, Netflix
Balázs Hidasi, GravityR&D
Craig Carmichael, Rovi
Emanuele Coviello, Keevio
Pádraig Cunningham, Insight Centre for Data Analytics
Joaquin Delgado, OnCue TV (Verizon)
Diana Hu, OnCue TV (Verizon)
Ben Jordan, Univ. of Minnesota
Brendan Kitts, Adap.tv (AOL)
Noam Koenigstein, Microsoft
Gert Lanckriet, UC San Diego
Hayim Makabee, Yahoo! Labs
Tom Rampley, Dish Network
Royi Ronen, Microsoft
Barry Smyth, Insight Centre for Data Analytics
Domonkos Tikk, GravityR&D
Ari Tuchman, quantiFind
Udi Weinsberg, Technicolor Labs
Esti Widder, Viaccess-Orca
Ho-Hsiang Wu, Rd.io
Dávid Zibriczky, ImpressTV
Jiayu Zhou, Samsung Research