Development of recommender system based on user and item data

With this project, we aim to increase our knowledge and experience in recommender systems. We are specifically interested in testing various data structures and algorithms that will allow us to provide recommendations to our users based on their interest (user-user), as well as the intrinsic similarities between different elements of our database (item-item). Based on our experience so far, none of the existing recommender system or algorithms can fully meet our requirements and existing datasets. The main goal is to develop new features of our web apps based on the results of this project. The main tasks to be performed include data analysis, literature review, algorithm development and testing.

Faculty Supervisor:

Yaoyao Fiona Zhao

Student:

Partner:

Turquoise Technology Solutions Inc

Discipline:

Computer science

Sector:

Artificial Intelligence; Information and Communications Technology; Technology

University:

McGill University

Program: