Statistical and Machine Learning with Applications to a Hybrid Recommender System for Retail Data

We are in the process of creating and growing a team of researchers expert in the field of machine learning and data-mining. Ultimately, our aim is to create solutions to eliminate the need to manually define personalization strategies. We are in the process of signing partnership agreements with retailers capable of collecting large-scale datasets of customer behaviour. Through a data-sharing/consulting partnership we plan to perform research on the design of recommender systems customized for the data-sets available to brick and mortar retailers. These methods can be used in their physical and online loyalty programs as well as in their dynamical promotions/pricing strategies.

Faculty Supervisor:

Sathish Gopalakrishnan;Alexander Rutherford;Robert Rohling;Tamara Munzner;Farouk Nathoo;Chi-Guhn Lee

Student:

Partner:

FIND Innovation Labs Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Simon Fraser University; The University of British Columbia; University of Toronto; University of Victoria

Program: