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| Content Provider | ACM Digital Library |
|---|---|
| Author | Sarukkai, Ramesh Rangarajan |
| Abstract | Users continue to have ubiquitous access to internet powered video content - giving them many choices for the media they choose to watch. However, even with the availability of millions of hours of internet video, consumers spend a significant amount of time on traditional TV - that too, despite lack of personalization and fixed set of mainstream content. Perhaps the reason for success of linear TV is its simplicity - you just turn it on if you want to spend an hour watching something with your friends or family and content just streams to you. In contrast, on the internet, we have a vast amount of diverse & unique video content, successful social networks for sharing this content, and fundamental technologies that personalize your experiences. Furthermore, with continued emergence of internet-connected TVs and devices that make IP delivered video easily accessible in your living room, the emerging problem is one of generating the perfect, personalized video stream - "Your Channel" in contrast to "A channel". How do we organize and build such a video stream that is relevant and interesting? In this talk, we will discuss experiments and solutions to creating this perfect video stream - how do we balance consistency with interestingness? How do we mesh social influence versus meta-data relevance? How we can leverage and learn from human curation? The talk concludes with a summary of challenges and opportunities for researchers working in the related areas of multimedia, search and social networks. |
| Starting Page | 45 |
| Ending Page | 46 |
| Page Count | 2 |
| File Format | |
| ISBN | 9781450301732 |
| DOI | 10.1145/1878151.1878165 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2010-10-25 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Linear tv Personalization Social media Video Iptv Video stream |
| Content Type | Text |
| Resource Type | Article |
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|---|---|---|---|
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