Jinni Offers Enhanced API, Builds in Social TV Recommendations
Movie and TV recommendation engine now works with live programming; offers sandboxing for UI testing.
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Jinni has announced an enhanced version of its API, letting TV and device makers add more personalization and social recommendation features to their movie and TV show guides. Jinni, a Tel Aviv, Israel-based company, creates search and discovery recommendations based on the viewer's mood and taste.
Capitalizing on one of the biggest trends in online video, the API now offers social recommendations from friends that also match the viewer's profile. Jinni doesn't rate all friend recommendations equally, but looks for taste matches. The company previewed this feature at CES, and is now releasing it.
Jinni can now recommend programming from live TV, a big step for a product that previously only offered video-on-demand and over-the-top content recommendations.
Finally, the enhanced API offers sandboxing, allowing cable providers to test user interface customizations before offering Jinni in their subscription packages.
"With the new API version, TV operators and CE manufacturers can now provide their customers with a more intuitive experience across various entertainment platforms, including live broadcasting, and enjoy the easy incorporation into existing platforms," says Yosi Glick, Jinni's co-founder and CEO.
Microsoft licensed Jinni's Semantic Discovery Engine and Entertainment Genome in September, 2011.
Speculation is that engine will power entertainment discovery on the Xbox, though Microsoft is mum.
Proposed interfaces show how Jinni's video recommendations could be used in different types of guides.
TV and online viewers can now get recommendations based on their moods or favorite plot elements directly from Jinni.