An ontology based semantic representation for Turkish Cuisine

Following recent advances in digital technologies, many data in various domains have been transformed into digital world and shared with millions of users via social media and web technologies. As a result, big amount of data has presented many challenging problems in different fields, e.g internet of things, artificial intelligence. One of application areas is in food domain. Recognition of food category from images, automatic recipe retrieval from internet and analysis and matching of food images with recipes, ingredients, nutrition values bring cooperation of multi disciplines and technologies. In this work, for the first time, semantical analysis of Turkish Cuisine is held and various information related to food in Turkish Cuisine is structured in a hierarchical ontology model. A new database containing 50 different food categories and related images is constructed and linked with data such as food properties, recipes, etc. As a result, multimodal information retrieval can be achieved faster in a more semantic way. At the same time, food image classification with deep learning methods is performed and faster connection of recognized food category to related semantic data is provided.