Category Archives: Conferences

1st Workshop on Recommender Systems for TV and Online Video – RecSysTV 2014

RecSysTV Program – 10th October 2014, Foster City, Silicon Valley, USA

Morning Session

  • 10:30-11:00 Morning Break

Mid-Morning Session

  • 11:00-11:15 A Graph-based Collaborative and Context-aware Recommendation System for TV Programs, E. Şamdan et al.
  • 11:15-11:30 Time-based TV Programs Prediction, R. Turrin et al.
  • 11:30-11:45 Augmented Matrix Factorization with Explicit Labels for Recommender Systems, J. Zhou et al.

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

Sponsored By:

2010 Summer Workshop of the Center for Language and Speech Processing

During the summer of 2010 I led a research team at the 2010 Summer Workshop of the Center for Language and Speech Processing at Johns Hopkins University. For 6 weeks we worked on combining text and video analysis to identify and localize complex actions in broadcast videos. You can find more detailed information about our project and our results here.