TECHNICAL WORKSHOP SERIES - Introduction to Recommender Systems a Comprehensive Overview - 1st in series (1st Offering) by: Bahareh Rahmatikargar

Tuesday, June 25, 2024 - 11:00

Technical Workshop Series

Introduction to Recommender Systems a Comprehensive Overview - 1st in series (1st Offering)


Presenter: Bahareh Rahmatikargar

Date: Tuesday, June 25th, 2024

Time:  11:00 AM

Location: 4th Floor (Workshop Space) at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)


Abstract: This workshop marks the first of a series of three workshops by Bahareh dedicated to the fascinating field of social network analysis and its application in recommender systems. In this initial session, I will provide a comprehensive overview of recommender systems, their applications, and their essential role across various domains.

We will start by exploring the concept of recommender systems, their fundamental principles, and their significance in enhancing user experiences. Beyond introducing the well-known types of recommender systems, I will also present an overview of several other types, including graph-based, sequential, session-based, cross-domain, and social recommender systems.

Throughout the workshop, we will address the unique challenges associated with each type of recommender system. While this session will primarily focus on theoretical aspects, the subsequent workshops in this series will offer practical insights and hands-on implementation of these systems.


Workshop Outline: After successful completion of this workshop, participants will be able to:

-Understand the fundamentals of recommender systems

-Identify the different types of recommender systems

-Comprehend the applications of recommender systems

-Recognize the challenges associated with recommender systems

-Prepare for the practical workshop


Prerequisites: None, however, this workshop is recommended for students interested in attending the others in this series.


Biography: Bahareh Rahmati is an enthusiastic Ph.D. student who has started her program at the School of Computer Science in January 2021. Her research is in the field of data science and AI, with focus on graph-based recommendation systems. She has currently published multiple papers in top-tier venues.


MAC STUDENTS ONLY - Register here

Note: This is a series of three workshops, students are encouraged to attend all, but it is not necessary in order to earn points. Registration in the rest of the series is NOT automatic, students will need to sign up using the link for MAC students.