Under Armour, Inc.
DEEP MULTI-MODAL PAIRWISE RANKING MODEL FOR CROWDSOURCED FOOD DATA

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.