Discover more projects across a range of sectors and discipline — from AI to cleantech to social innovation.
Layer 6 builds state-of-the-art recommender systems for TDs online businesses. Collaborative Filtering (CF) is a common recommendation approach that widely adopted by many e-commerce platforms. Modern CF algorithms attempt to exploit latent features to represent users and items, which can lead to the lack of transparency of the recommender systems. In order to build a trustworthy recommender system, it is necessary to provide explanations associated with each recommendation so that users can understand why a specific item has been suggested. The proposed research project would explore the potential of combining sequence-to-sequence (seq2seq) natural language generation models with collaborative filtering techniques into a multi-task learning setting. The result would be a recommender system that could predict customers needs with a high degree of accuracy, while producing effective, personalized explanations. Such explainability would build trust between the recommender system and TDs customers, and accordingly drive sales and customer loyalty.
Layer 6 AI
Information and communications technologies
Find the perfect opportunity to put your academic skills and knowledge into practice!Find Projects
The strong support from governments across Canada, international partners, universities, colleges, companies, and community organizations has enabled Mitacs to focus on the core idea that talent and partnerships power innovation — and innovation creates a better future.