Say hello to Ness, a mobile app that can figure out which restaurants you'll enjoy the most, based on your personal tastes. The app, now available in the iOS App Store (U.S.-only), takes a different approach to restaurant recommendations than Yelp, UrbanSpoon and the regular tools people usually use to choose where they will dine. And Ness Computing, the company behind the app, hopes that its unique approach can also change how we shop, discover music and more.
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Ness, at its core, is a recommendation engine. Users open the iOS app and quickly rate different restaurants nearby on a scale of one to five stars. After ten ratings, the app has enough data to deliver a set of nearby restaurants it believes you will like, based on your personal tastes and preferences.
The technology behind Ness is the key to the app's functionality. Ness is powered by a proprietary technology called the Likeness Engine. It takes in information from a variety of sources, including Facebook, Foursquare, friend recommendations, restaurant popularity and personal tastes preferences to figure out whether you're going to be interested in a restaurant on a scale of 0-100%.
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Ness was developed over several years by a team backed by Khosla Ventures, Alsop Louie Partners, TomorrowVentures, Bullpen Capital and one of Palantir's co-founders. The team utilized machine learning and natural language processing technology to create a recommendation engine that could cut through the noise of sifting through search results.
The app has come a long way since its previous incarnation (an app called Trumpet). We've played around with this app, and we've been impressed by the results so far. We've also heard stories of the technology being able to figure out your musical tastes just by looking at information in your Facebook profile.
If Ness can nail down restaurant recommendations, it has the opportunity to become a new type of mobile search engine that can be used for almost any decision.
This story originally published on Mashable here.
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