Interactive preference elicitation application for book recommendations

Kobo is an online e-book retailer that provides recommendations for future purchases to its user base. One difficulty that recommendation systems face is what is known as the “cold-user” problem. In this scenario, when we know so little of a user’s preferences (for example, if they are new to the platform), we do not have any basis for recommendations. The goal of this project is to develop an interactive application that can elicit such preferences from users about whom we have little information, and that can help improve recommendations for power users. For new users, the preference elicitation process during onboarding can help them find books of interest much faster; for established users, it gives them the ability to refine their recommendations. Such improvements facilitate a more streamlined discovery experience.

Faculty Supervisor:

Scott Sanner

Student:

Partner:

Rakuten Kobo Inc.

Discipline:

Computer science

Sector:

Information and Communications Technology; Entertainment and Media

University:

University of Toronto

Program: