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AI and automation make perfect marriage for deep metadata

Video search and recommendation have been held back by lack of detailed metadata, which often offers little more than title, genre, length, time of creation and some credits including director, actors and other participants. Fortunately times are changing as metadata starts to dig deeper and allow recommendations engines to pick up more nuanced information down to scene level and some of the bit part players. This promises not only to match content as a whole more accurately to viewer preferences and profiles, but also to allow micro level extraction down to scenes with potential even for creating and serving personalized extracts or trailers. On the one hand new content is already being created automatically with more information from cameras for…

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