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    RJI Futures Lab #183: Personalized Content Discovery with CogniK

    by Rachel Wise
    February 24, 2017

    CogniK is a start-up that helps media companies personalize content discovery for their users by enabling them to incorporate a customized recommendation engine. According to George Jeng, vice president of product at CogniK, the engine uses machine learning and semantic analysis to automatically tag and characterize stories, and then link together related material.

    Reporting by Reuben Stern and Xin Liu


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    • To power the recommendation engine, CogniK combines data about user behavior with input from the media company client, enabling each media company to adjust the way the engine works.
    • The CogniK system can be integrated into apps, websites or backend programs.
    • According to the CogniK site, there are three keys to their system: automated tagging, personalized search, and discovery and recommendations.
    • The team has recently launched a personalized news bot called Vincent. According to this post on Medium, Vincent was “developed on the Telegram messaging platform to allow users to select topics from current events and receive a personalized recommendation of the latest news topics that fit their preference.”

    Rachel Wise is an editor at the Futures Lab at the Reynolds Journalism Institute and co-producer of the weekly Futures Lab video update.

    RJI Futures Lab web bannerThe Reynolds Journalism Institute’s Futures Lab video update features a roundup of fresh ideas, techniques and developments to help spark innovation and change in newsrooms across all media platforms. Visit the RJI website for the full archive of Futures Lab videos, or download the iPad app to watch the show wherever you go. You can also sign up to receive email notification of each new episode.

    Tagged: cognik content discovery data user behavior

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