Baboonr - Relevant & Personalized related content is just one click away!

Baboonr - Relevant & Personalized related content is just one click away!

Organisation: Yournalism (Netherlands)

Publication Date: 04/10/2015


Today, if you desperately want more on the topic you are reading about, it is really hard to find relevant related news content based on your exact needs, without loosing your attention. Where do you possibly find specific and personalized content, without losing your attention to what you were consuming?! All newssites have plugins with “relevant content” next to an article. And they all suck. It’s only the old stuff from the same website, often not all that relevant at all. That's why our challenge during the GEN Editors Lab at NOS in Hilversum was: How can we retrieve the most relevant, personalized news content with just ONE CLICK? So fast, it’s impossible to lose your attention. We built Baboonr. It lends its name from the baboon, a dominant creature that marks out its entire territory (internet), scraping all surface to opportunistically and selectively find all there is to consume. If you’re looking for something in the same territory, the Baboon probably already has found it. We built a prototype that allows the user to find the most relevant related content with just one click. Just select an article, or even just a sentence from an article, and Baboonr will do the rest. Content can be personally filtered by duration and type of media content. Eventually Baboonr is able to learn and adapt to your preferences. Right now, the main features work, (See We also designed a unique and brand new newsexperience. In the Baboonr app, content is presented based on a curation of user curiosity. Crowdsourced fascination, if you want. You can select or search to dive deeper and deeper into all related content. By using iOS’s Location Services or Google Now, the app instantly knows what type of content (long or short, video or text) you want based on your whereabouts and agenda. Baboonr is for the type of news consumer that wants its news in his preferred shape and size. On the other hand, Baboonr is for those who never think they have read or watched it all and want to know everything there is about a topic. Future developments (see slides): -Improvement of Natural Linguistic Programming, for more contextual search (better results) -Media companies push their content to us, we make sure their content is related so they have more traffic (Affiliate marketing Businessmodel, plus we have faster and more efficient search results) -We gain interesting consumer insights, based on user’s curiosity and fascination. We learn from their mediaconsumption related to their whereabouts, preferences and consuming behavior in the Baboonr Environment. Team: Daan Keuper (Developer) Laurens Haan (Designer) Huub Schuijn (Online editor in chief)

Technologies used for this project:

Natural linguistic programming with use of Entity recognition. We run a live scraper with an algorithm similar to that from Google News, but with Baboonr you now you can filter on duration (long, short, medium) , type of media (Audio, video, text). With the chrome extension you can select a sentence in your browser, and Baboonr recognizes the names, places and important key words. These will be the search words for the search engine scraper. Results come from all the big news sites like BBC, CNN, REUTERS, BLOOMBERG, Washington Post, Guardian, but also videosites like Youtube. Developed in Python and Java. The clickable mockup of our mobile app is designed in Sketch. Presentation made in Keynote.


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