Date of Award
6-11-2021
Document Type
Thesis - SCU Access Only
Publisher
Santa Clara : Santa Clara University, 2021.
Department
Computer Science and Engineering
Abstract
Current recipe recommendations systems primarily utilize elements such as ingredients and user ratings in order to give new recommendations to users. However, specific flavor profiles such as sweetness, saltiness, and richness do not play a significant enough role in these recipe suggestions. With TasteMate, we aim to improve current recommendation systems by creating an application that utilizes a link between the nutrition facts of a dish and different flavor profiles. Our goal is to create a personalized flavor based recipe recommendation system that uses a user’s taste profile to provide the best matching food recipes.
Recommended Citation
Codipilly, Darren; Quant, Brandon; and Xiao, Horatio, "TasteMate" (2021). Computer Science and Engineering Senior Theses. 213.
https://scholarcommons.scu.edu/cseng_senior/213
SCU Access Only
To access this paper, please log into or create an account in Scholar Commons using your scu.edu email address.