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An automatic news video parsing, indexing and browsing system
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Learning video browsing behavior and its application in the generation of video previews
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Assessing tools for use with webcasts
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Social navigation in web lectures
Proceedings of the seventeenth conference on Hypertext and hypermedia
Community annotation and remix: a research platform and pilot deployment
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Watching together: integrating text chat with video
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Why we tag: motivations for annotation in mobile and online media
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Exploring social dynamics in online media sharing
Proceedings of the 16th international conference on World Wide Web
CHI '08 Extended Abstracts on Human Factors in Computing Systems
Watch-and-comment as a paradigm toward ubiquitous interactive video editing
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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Proceedings of the 1st international conference on Designing interactive user experiences for TV and video
Enhancing social sharing of videos: fragment, annotate, enrich, and share
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Less talk, more rock: automated organization of community-contributed collections of concert videos
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VideoSkip: event detection in social web videos with an implicit user heuristic
Multimedia Tools and Applications
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This paper presents a high-level overview of Yahoo Research Berkeley's approach to multimedia research and the ideas motivating it. This approach is characterized primarily by a shift away from building subsystems that attempt to discover or understand the "meaning" of media content toward systems and algorithms that can usefully utilize information about how media content is being used in specific contexts; a shift from semantics to pragmatics. We believe that, at least for the domain of consumer and web videos, the latter provides a more promising basis for indexing media content in ways that satisfy user needs. To illustrate our approach, we present ongoing work on several applications which generate and utilize contextual usage meta-data to provide novel and useful media experiences.