Jinni (search engine)
Media & Entertainment | |
Founded | January 2008 |
Products | Discovery service for movies, TV shows, other media |
Website | Jinni.com |
Jinni is a search engine and recommendation engine for movies, TV shows and short films. The service is powered by the Entertainment Genome, an approach to indexing titles based on attributes like mood, tone, plot, and structure. Its availability is via API, in business-to-business licensing, where it impacts businesses like Comcast's Xfinity product (and others whose capabilities benefit from smart entertainment search).
Description
The Jinni service included semantic search,[1] a meaning-based approach to interpreting queries by identifying concepts within the content, rather than keywords. The search engine provided a taste-based video discovery experience by mood, plot and other parameters, and included options to browse and refine with additional terms – for example “action in a future dystopia” or “like: Beautiful Girls, funny.”[2]
Jinni's semantic discovery engine was powered by the Entertainment Genome™, containing thousands of "genes" that are automatically assigned to describe mood, style, plot and setting to every released movie or TV show. These elements were then matched to subscribers' personal tastes according to their viewing history in order to provide a truly personalized discovery experience. Jinni also provided recommendations, according to a given user's favorites and ratings of movies and TV shows.[3] The recommendations were based on content and on the user's taste profile.[4]
As well as discovery, the Jinni website included Internet television, the online streaming of film and TV, mostly only available in the US, e.g. via Hulu. Jinni also linked to other sites that rent or sell DVDs or offer downloading or streaming for a fee, such as Netflix, Amazon and Blockbuster.[1]
Jinni's technology involved a taxonomy created by film professionals, with new titles indexed via Natural Language Processing and Machine Learning methods to automatically analyze reviews and metadata.[5]
Jinni's products included the website and APIs for TV operators and Internet content providers.[5] Jinni's partners include SeaChange,[6] NDS,[7] and OpenTV.[8]
The company recently ended its public service in order to focus solely on the ADTECH space with an entertainment audience targeting solution addressed to movie studios, TV networks and OTT video providers.
History
Jinni was founded in January 2008. Jinni has raised $2.6 million in Round A and seed funding from DFJ Tamir Fishman, Startup Factory and private investors.[9]
In March 2009, the Jinni website integrated with the Netflix developer API. In consequence, people can search the Netflix catalog and Instant Watch catalog from Jinni, and add to their Netflix queues or begin streaming.[10]
In May 2010, Google announced a strategic alliance with Jinni for Google TV.[11]
In May 2011, Jinni announced $5 Million Round B Funding.[12]
In June 2012, Belgian cable operator Belgacom deployed a recommendation engine from Jinni on digital set-tops that allows subscribers to browse for content based on mood.[13]
In July 2012, Jinni, the semantic television discovery engine, recently teamed up with Swisscom “for integration into On Demand and live TV.[14]
On November 6, 2013, Jinni launched its new customer facing website and iPad application, providing personal recommendations based on a users Entertainment Personality, personalized TV listings, semantic content searches and social based group recommendations.[15]
In May of 2014, Jinni integrated its mood and taste-driven video discovery engine with AT&T’s U-verse TV platform. [16]
In June 2015, Jinni shut down its public service and now offers "solutions for pay TV & OTT operators" and "for entertainment advertisers".[17][18]
References
- 1 2 "Archived copy". Archived from the original on 2009-03-29. Retrieved 2009-03-26.
- ↑ Schroeder, Stan. "Jinni's Semantic Movie Search Now Works With Netflix". mashable.com. Retrieved 26 December 2016.
- ↑ Ostrow, Adam. "Jinni's Genius Way to Recommend Movies". mashable.com. Retrieved 26 December 2016.
- ↑ Pash, Adam. "Jinni Recommendation Service Like Pandora for Movies". lifehacker.com. Retrieved 26 December 2016.
- 1 2 "Archived copy". Archived from the original on 2009-02-04. Retrieved 2009-01-22.
- ↑ tracyswedlow (9 September 2009). "SeaChange Incorporates Jinni's Search-and-Recommendation Engine into its VOD Platform". itvt.com. Retrieved 26 December 2016.
- ↑ Albrecht, Chris (3 November 2009). "NDS Adds Jinni for Video Recommendations". newteevee.com. Retrieved 26 December 2016.
- ↑ "OpenTV, Jinni Team on Search - Light Reading". lightreading.com. Retrieved 26 December 2016.
- ↑ "Jinni - crunchbase". crunchbase.com. Retrieved 26 December 2016.
- ↑ "Jinni searches Netflix better than Netflix". cnet.com. Retrieved 26 December 2016.
- ↑ Wauters, Robin. "Jinni Is Building A Smart 'Taste Engine' For Google TV (Screenshots)". techcrunch.com. Retrieved 26 December 2016.
- ↑ Tsotsis, Alexia. "Movie And TV Show Recommendation Engine Jinni Raises $5 Million". techcrunch.com. Retrieved 26 December 2016.
- ↑ "Jinni deploys mood-based program guide on Belgacom set-tops - FierceCable". fiercecable.com. Retrieved 26 December 2016.
- ↑ "Jinni Teams with Swisscom for Integration into TV - DATAVERSITY". semanticweb.com. 12 July 2012. Retrieved 26 December 2016.
- ↑ "The Video Recommendation Engine Behind The Xbox Launches A Standalone iPad App". fastcompany.com. 5 November 2013. Retrieved 26 December 2016.
- ↑ "AT&T U-Verse Revs Up Jinni’s Video Discovery Engine - Multichannel". multichannel.com. Retrieved 26 December 2016.
- ↑ "Find movies, TV shows matching your taste and watch online - Jinni". 28 June 2015. Archived from the original on 28 June 2015. Retrieved 26 December 2016.
- ↑ "Jinni Entertainment Discovery & Targeted Ads". jinni.com. Retrieved 26 December 2016.
External links
- Official website
- Top 10 Movie Recommendation Engines - CNET
- Red Herring Europe 100 Winners 2009
- SXSW Web Awards Finalists 2009
- Plugg Rally Winners 2009
- CableLabs Best Product Idea Winner 2010
- Webby Honorees 2010