Abstract: A method and system for providing more relevant search results and recommendation from a food database is disclosed. The method includes receiving a query, a first candidate food, and a second candidate food. The method includes generating text feature vectors based on the query and food names of the first and second candidate foods using at least one first embedding function of a machine learning model. The method includes determining nutrition content vectors from the nutritional data of the first and second candidate foods. The method includes generating a nutrition content vector based on the query using a second embedding function of the machine learning model. The method includes determining which of the first and second candidate food is more relevant to the query based on the text feature vectors and the nutrition content vectors. The method includes providing search results or recommendation based on the determined relevance.

Abstract: A system and method of providing nutritional data for a user is disclosed herein. The method includes receiving a selected restaurant from a personal electronic device, and providing menu data for the user based on the selected restaurant. The method further includes receiving a selected menu item from the personal electronic device, associating the selected menu item with a plurality of food items in a database, and providing the plurality of food items for the user. Furthermore, the method includes receiving a selected one of the plurality of food items from the personal electronic device, and providing nutritional data based on the selected one of the plurality of food items.

Abstract: A method of operating a health tracking system is disclosed. The method comprises: receiving a first data record comprising at least a first descriptive string regarding a consumable item, the first descriptive string having at least one word thereof incorrectly spelled; generating a vector using the first descriptive string using a machine learning model; identifying a second descriptive string which corresponds to the consumable item and which has a correct spelling of the at least one incorrectly spelled word by applying the machine learning model to the generated vector; calculating a confidence factor regarding the identified second descriptive string using the machine learning model; and when it is determined that the confidence factor exceeds a predetermined threshold, (i) modifying the first data record by replacing the first descriptive string with the second descriptive string, and (ii) storing the modified first data record in the database.

Abstract: System and method for associating user-entered consumable item description to an entry in a consumable item database. In one embodiment, formally structured restaurant menu item is matched to a large database of food items that has been constructed via crowd-sourcing. A novel, practical, and scalable machine learning solution architecture, consisting of two major steps is utilized. First a query generation approach is applied, based on a Markov Decision Process algorithm, to reduce the time complexity of searching for matching candidates. That is then followed by a re-ranking step, using deep learning techniques, to ensure matching quality goals are met.

Abstract: System and method for associating images to recipe records. In one embodiment, a method is provided which includes: receiving an uploaded photograph of a recipe image; and searching a database for an image which matches to the uploaded image. The database search may, in one embodiment, make use of a convolutional neural network (CNN)-based classifier. When one of the records in the database is identified as matching, providing a portion of the data associated to the record to the user device; receiving feedback from the user; and based on the feedback, providing a remaining portion of the data associated to the identified record to the user device for logging thereat; or enabling the user to create a new consumable item record.

Abstract: A method for operating a health tracking system, a health tracking system, and non-transitory computer-readable medium for operating a health tracking system are disclosed. The method comprises receiving a data record comprising at least a descriptive string and nutritional data regarding a consumable item to which the data record corresponds; determining a taste associated to the consumable item based on an evaluation of at least one of: (i) the descriptive string, and (ii) the nutritional data; and associating the determined taste with the data record in a database.

Abstract: A health tracking system includes a plurality of health tracking devices in communication with a host server. In one embodiment, a method of operating the system comprises: receiving data relating to consumables from user devices; storing the data as data records; grouping the data records into groups based on a description string of each; determining an individual score to associate to each data record; and applying an identifier to one of the data records in each group, the one of the data records comprising a one associated with a high score relative to the remaining ones of the data records in the group.

Abstract: A method for decreasing a number of individual entries in a database of user-created records which describe a single item by: receiving a plurality of user-created records, each of said records comprising at least a descriptive string; placing individual ones of the plurality of user-created records having a sufficiently similar descriptive string into one of a plurality of first groups; hashing the descriptive string of each of the plurality of first groups in order to place two or more groups into a single bin; performing a pair-wise comparison of the descriptive strings of the two or more groups in each bin; and when the comparison of the descriptive strings of the two or more groups in a bin results in a distance below a first threshold, merging the two or more groups into a combined group.

Abstract: A system and method of providing nutritional data for a user is disclosed herein. The method includes receiving a selected restaurant from a personal electronic device, and providing menu data for the user based on the selected restaurant. The method further includes receiving a selected menu item from the personal electronic device, associating the selected menu item with a plurality of food items in a database, and providing the plurality of food items for the user. Furthermore, the method includes receiving a selected one of the plurality of food items from the personal electronic device, and providing nutritional data based on the selected one of the plurality of food items.