Ness Launches Personal Search Engine for Restaurants

8/26/2011
Ness Computing’s personal search engine app for iPhone and iPod touch, called Ness, is now available on the App Store as a Featured App. Instead of providing a long list of reviews to sift through, Ness recommends restaurants based on the learned likes and dislikes of each individual, as well as his or her friends. The result is search that is tailored to each person, for more relevant recommendations and quicker decisions on the go.
 
Ness is driven by the company’s internally developed Likeness Engine, which uses collaborative filtering, social graph data mining, and natural language processing. To make recommendations, Ness weighs information from many different sources, including a person’s taste profile, his or her similarity to other users, the total popularity of each restaurant, and trusted recommendations from friends on third-party services like Facebook and Foursquare. Ness then computes a Likeness Score of 0-100% that predicts how much the person will enjoy each recommended restaurant. Since different people decide where to eat using different criteria (an intricate balance of personal taste, recommendations from friends, location, ambience, and other factors), each person’s results are unique to them. The more a person uses Ness, the more personalized it is to their tastes. Ness embraces a detail driven design philosophy and explores the full visual capabilities of iOS with a beautiful interface designed to help people quickly decide where to eat on the go.
 
Ness is designed for people who love food.
  • The Social Butterfly: Ness connects to Facebook and Foursquare, and so that users can see their friends’ recommendations and check-ins directly on the Ness search results page. They can keep up-to-date with their latest restaurant discoveries on the Ness newsfeed. For those with an extensive social network, Ness lets users select which friends they’d like to follow so that they are heard above the noise.
  • The Foodie: Users can see how likely they are to enjoy each restaurant with the Ness Likeness Score. If they’re bored with the places that they usually frequent, they can use the “Hide Places I’ve Rated” filter to let new restaurants bubble to the top. If supporting small businesses is important, users can user the “No Big Chains” filter to find unique local eateries.
  • The Frequent Diner: Ness knows its users, so there’s no need to waste time sifting through pages of reviews. Guests can turn on the distance filter and immediately see what nearby restaurants they’re most likely to enjoy. Ness remembers favorite cuisines, so it shows users where to find comfort food when they’re in a new city. Or, for the more adventurous, try one of the restaurants marked as a local favorite. In future releases,
Ness will extend its offering to other lifestyle categories, including music, shopping, nightlife, and entertainment, all within the same app.
 
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