TipSense, LLC today announced the launch of dishtip.com, which allows users to search for specific food dishes, such as ‘french toast’, ‘chicken wings’ or ‘tuna tartare’, in order to discover the top dishes and corresponding restaurants. An intelligent web 3.0, semantic-focused mashup, dishtip performs a deep analysis of millions of web based-reviews, photos and content to provide suggestions for the best dishes, offer related search items, as well as filter by such categories as food taste, price and cuisine.
Users can also search by cuisine, such as ‘Chinese’ or for dishes containing a specific food ingredient, such as ‘nutella’ or ‘curry’. A search on a specific restaurant will identify the top rated dishes to order at that location. Whether a user searches by food item, cuisine, restaurant or taste, dishtip always provides specific dish recommendations for that given category.
“Our goal is to provide a destination that greatly enhances the way people search for food dishes, enabling them to discover the very best dishes and restaurants,” said David Schorr, Founder of the dishtip.com website. “We’ve harnessed vast amounts of web content and analyzed the data with sophisticated semantic mining and natural language processing technologies. dishtip will help people discover amazing dishes.”
One of the key features making dishtip so unique is food ‘discovery’. Using a multifaceted classification scheme, dishtip analyzes multiple data points about a dish or search term to offer suggestions. For example, by analyzing a search for ‘chicken wings’, dishtip might predict that the user may also be interested in other dishes related to ‘poultry’, ‘spicy’, ‘BBQ’, ‘finger foods’ or ‘savory’. In essence, the user is on a journey during the search process that often leads to the discovery of dishes and corresponding restaurants that would otherwise have remained unknown.
Another differentiator is the innovative image processing and classification technology that delivers an unsurpassed user experience by providing a picture of the specific dish being suggested. Seeing photos of actual dishes adds a critical visual perspective to help users make better decisions about what to eat and where to get it.