RecSysTV 2016 - 3rd Workshop on Recommender Systems for Television and Online Video (RecSysTV 2016)

3rd Workshop on Recommender Systems for Television and Online Video
http://www.recsys.tv
We are pleased to invite you to participate in the 3rd Workshop on Recommender Systems for Television and Online Video (RecSysTV 2016) that is happening in conjunction with the ACM RecSys 2016 conference in Boston, MA from September 15th-19th 2016.
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 (on premise or in the cloud) and the traditional linear TV. In addition, consumers can also access the content not just on the big screen, but also on their computers, phones, and tablet devices.
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. For example, the content available on linear channels is constantly changing and often only available once which leads to severe cold start problems and we often consume TV in groups of varying compositions (household vs individual) which makes building taste profiles and modeling consumer behavior very challenging.
We encourage participation along several themes which include but are not limited to:
** Context-aware TV and online video recommendations
* Leveraging contextual viewing behaviour, e.g. device specific recommendations
* Mood based recommendations
* Group recommendations
** User modeling & leveraging user viewing and interaction behavior
* How can social media improve TV recommendations
* Cross-domain recommendation algorithms (linear TV, video on demand, DVR, gaming consoles)
* Multi-viewer profile separation
* Evaluation metrics for TV and online video recommendations
** Content-based TV and online video recommendations
* Analysis techniques for video recommendations based on video, audio, or closed caption signals
* Utilization of external data sources (movie reviews, ratings, plot summaries) for recommendations
** Other topics related to TV and online video recommendations
* Video playlisting
* Linear TV usage and box office success prediction
* Catch-up TV recommendations
* Personalized advertisement recommendations
* Recommendations of 2nd screen web content
* Recommendations of short form videos (previews, trailers, music videos)
IMPORTANT DATES
- Submission deadline: June 24, 2016
- Notification: July 15, 2016
- Camera-ready: July 22, 2016
- Workshop date: September 15, 2016 (full day)
SUBMISSION INFORMATION
We are soliciting submissions of long and short papers, as well as position presentations.
Long paper are to represent original mature research and can be 6-8 pages long. We request potential submitters to adhere to double-column ACM SIG format in line with standard RecSys formatting guidelines.
Short papers are to represent early/promising research, demos or industrial case studies and can be 4 pages in length (ACM RecSys style) or up to 20 slides.
Use the following website to electronically submit your paper: https://cmt3.research.microsoft.com/RECSYSTV2016
Note that attendance at the workshop requires registration for the ACM RecSys 2016 conference as a whole. This year there is no separate registration for workshops. Each accepted workshop paper must register at least one author at the conference.
ORGANIZING COMMITEE
Jan Neumann, Comcast Labs, Washington, DC (jan_neumann-AT-cable.comcast.com)
John Hannon, Zalando SE (john.hannon-AT-zalando.ie)
Claudio Riefolo, ContentWise, Milan, Italy (claudio.riefolo-AT-contentwise.tv)
Hassan Sayyadi, Comcast Labs, Washington, DC (hassan.sayyadi-AT-cable.comcast.com)
PROGRAM COMMITEE
Hidasi Balazs, GravityR&D
Justin Basilico, Netflix
Craig Carmichael, Rovi
Humberto Corona, Zalando
Paolo Cremonesi, Politecnico di Milano
Joaquin Delgado, OnCue TV (Verizon)
Diana Hu, OnCue TV (Verizon)
Brendan Kitts, Adapt.TV (AOL)
Gert Lanckriet, UC San Diego
Rani Nelken, Outbrain
Royi Ronen, Microsoft
Barry Smyth, Insight Centre for Data Analytics
Esti Widder, Viaccess-Orca
David Zibriczky, ImpressTv
For up to date information about the workshop, please see the workshop website at www.RecSys.tv