Jinni uses innovative semantic technology to help people choose what to watch next. Jinni’s premise is that understanding taste is the key to helping people find movies and TV shows they’ll love. To celebrate our public beta launch, we’re proud to be making a donation to Best Friends Animal Society, the largest no-kill animal rescue organization in the US.
As part of our “Watch movies for a change” campaign, we’ll donate $10,000 to Best Friends based on sign-ups for Jinni.
Excellent! Please sign up for Jinni here while you’re reading this post, don’t put it off!
Jinni addresses the twin entertainment trends of on-demand and personalization. While methods for accessing video content have greatly advanced, methods for people to figure out what they actually want to watch are lagging.
Jinni’s semantic search and personal recommendations help users make sense of all the movies, shows and semiprofessional video out there with a one-stop service for choosing and getting linked to watch. Exploring flexibly and intuitively in Jinni’s visual interface, users shift focus from what’s popular to what fits their moods and tastes.
Alongside the destination website, Jinni offers APIs for Internet content providers and TV operators.
The core IP powering the Jinni.com service is the Movie Genome, containing several thousand genes. These are assigned to each title to describe plot, mood, style, setting, soundtrack and more – a rich alternative to the usual genre language.
The Movie Genome taxonomy was created by film professionals. New titles are automatically indexed via analysis of user reviews and metadata, using a proprietary Natural Language Processing solution. This automated process offers consistency, efficiency, and a diversity of viewpoints from analyzing many user reviews.
Taste Profiling: We’ve expanded the intelligent features of our Taste Engine, as an aid to personalized discovery. The Movie Personality Sketch is a visual presentation of users’ unique movie tastes and – if we are what we watch – personalities. The Match-o-mat identifies compatibility between users: e.g. “You both especially like touching and sentimental stories about looking for love and unlikely couples.”
Community: Jinni isn’t a social network, it’s an internet application designed to fit how people relate to entertainment. Since conversation is part of that, we’re introducing tools to discover people with shared tastes, view friends’ recommendations, and more.
Pulse: Discussion of movies and shows is taking place around the web – e.g. on Twitter, Facebook, and personal blogs. We see Jinni as part of this conversation, and are rolling out options for people to share from Jinni to other sites, and vice versa. We’re also introducing the Jinni Pulse, live streams of users’ actions and opinions. Catalog: We’re now at 30,000 titles, and growing!
Core Features:
Semantic Search: Type “thought-provoking sci-fi” or “action with a surprise twist” in the search box – and get real results.
Personalized Recommendations: Jinni generates recommendations using a unique model of each person’s taste. (Unlike collaborative filtering methods on Amazon, Netflix – the familiar “People who like this also like –“)
Integration with leading content providers: Seamless discovery from Jinni over catalogs of Netflix, Hulu, and more.
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Source: Jinni.com
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