Design of the next-generation of content-based, context-aware product recommender systems

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 working with more than 1000 retail locations across North America and collecting large-scale datasets of customer behaviour. Through a data-sharing/consulting partnership we plan to perform research on the design of recommender systems and predictive models customized for the datasets available to retailers. These methods can be used in their physical and online marketing programs as well as in their dynamical promotions/pricing strategies.

Faculty Supervisor:

Jiannan Wang

Student:

Tommy Betz

Partner:

FIND Innovation Labs Inc.

Discipline:

Computer science

Sector:

University:

Program:

Accelerate