Please note: This PhD seminar will be given online.
Ivens Portugal, PhD candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Paulo Alencar, Donald Cowan, Daniel Berry
Recommender systems use algorithms to provide users with product or service recommendations. Recently, these systems have been using machine learning algorithms. However, choosing a suitable machine learning algorithm for a recommender system is difficult because of the number of algorithms described in the literature. Researchers and practitioners developing recommender systems are left with little information about the current approaches in algorithm usage. Moreover, the development of recommender systems using machine learning algorithms often faces problems and raises questions that must be resolved.
In this seminar, I will present a systematic review of the literature that analyzes the use of machine learning algorithms in recommender systems and identifies new research opportunities. I will discuss (i) trends in the use or research of machine learning algorithms in recommender systems; (ii) open questions in the use or research of machine learning algorithms; and (iii) how new researchers can position new research activity in this domain appropriately. The results of the review include to identify existing classes of recommender systems, characterize adopted machine learning approaches, discuss the use of big data technologies, identify types of machine learning algorithms and their application domains, and analyzes both main and alternative performance metrics.
To join this PhD seminar on Zoom, please go to https://uwaterloo.zoom.us/j/93657156063?pwd=aWQvb3dTWDJLSG9QaEQ3dmkxOVA2dz09.
200 University Avenue West
Waterloo, ON N2L 3G1