SEARCH: Results Tailored to a Person’s Tastes

Yet another location based app has been launched, this time it is by a California based startup called Ness Computing. According to Ness Computing what makes this app different is that it is a personal search engine. The app is for iPhone and iPod touch and is now available on the App Store as a Featured App.

The app, called Ness, distigushes itself in three ways: (1) results are tailored to each individual person’s preferences rather than one-size-fits-all, (2) Like Google’s social search, content is from trusted friends rather than strangers, and (3) the app intelligently adapts to a person’s unique tastes over time.

The first category Ness supports is restaurants. 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.

Compared to existing search engines, Ness is more.

Existing search and recommendation services simply aggregate reviews from strangers without regard to the tastes and preferences of the person doing the search. Under the current search paradigm, ten different people looking for Italian restaurants in San Francisco all receive the same set of results.

Ness moves far beyond this, by delivering a personally relevant experience driven by mobile and social data.

Ness makes a leap forward in technology.

Ness is driven by the company’s internally developed Likeness Engine, which uses advanced techniques in machine learning (including 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: Connect Ness to Facebook and Foursquare, and see your friends’ recommendations and checkins directly on the Ness search results page. Keep up-to-date with their latest restaurant discoveries on the Ness newsfeed. For those with an extensive social network, Ness lets you select which friends you’d like to follow so that they are heard above the noise.
• The Foodie: See how likely you are to enjoy each restaurant with the Ness Likeness Score. If you’re bored with the places you usually frequent, use the “Hide Places I’ve Rated” filter to let new gems bubble to the top. If supporting small businesses is important to you, use the “No Big Chains” filter to find unique local treasures.
•  The Frequent Diner: Ness knows you, so there’s no need to waste time sifting through pages of reviews. Just turn on the distance filter and immediately see what nearby restaurants you’re most likely to enjoy. Ness remembers your favorite cuisines, so it shows you where to find comfort food when you’re in a new city. Or, for the more adventurous, try one of the restaurants marked as a local favorite.

In future releases, Ness plans to extend its offering to other lifestyle categories, including music, shopping, nightlife, and entertainment, all within the same app.

The Ness App is available for free from the App Store on iPhone and iPod touch or at likeness.com/app.