TV Answers - Using the Wisdom of Crowds to Facilitate Searches with Rich Media Context

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.