Television has always been a popular entertainment medium with considerable impact on consumer purchase behaviors. However, unlike mobiles and PCs, it has yet to support an explicit search capability that extends beyond simple content navigation. A core reason for this is lack of usable input interfaces for TV coupled with the difficulty of creating and executing queries based on rich media context. In this paper, we present TV Answers -a system that combines a novel context capture capability (Freeze-Frame) with an intelligent web services mediator (Edge Proxy) to "crowd-source" user-generated queries. We describe the design and implementation of an early prototype of TV Answers and highlight the challenges and opportunities presented by such systems. Our goal is to demonstrate the viability of using "social search" as a complement to existing algorithm-driven search solutions for rich media consumption.
Television and video consumption are growing ra p idl y worldwide, drivin g usa g e of second and third screens for related interactions and information. Since television has a p roven im p act multi-tasking behaviors and leads to attention fragmentation.
While networked devices have been proliferating in the home, the systems utilizing them typically operate in isolation from each other. This is partly due to the lack of a common framework that facilitates the exchange of information across these systems. Hence, we envision a home and person focused extensible event framework that provides a platform for dissemination, storage, and retrieval of events generated by such networked devices, and facilitates the extraction of high level semantics information through the application of event fusion algorithms. This will enable the delivery of personalized and relevant information to the users, and provide opportunities for new services activated by intelligent events.
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