NFARec: A Negative Feedback-Aware Recommender Model - Recommendation Systems
Offered By: Association for Computing Machinery (ACM) via YouTube
Course Description
Overview
Explore a cutting-edge recommender model in this 14-minute conference talk from SIGIR 2024. Delve into NFARec, a Negative Feedback-Aware Recommender Model presented by authors Xinfeng Wang, Fumiyo Fukumoto, Jin Cui, Yoshimi Suzuki, and Dongjin Yu. Learn how this innovative approach incorporates negative feedback to enhance recommendation systems, potentially improving user experience and recommendation accuracy. Gain insights into the latest advancements in recommendation technology and understand how negative feedback can be leveraged to create more personalized and effective recommendations.
Syllabus
SIGIR 2024 M3.5 [fp] NFARec: A Negative Feedback-Aware Recommender Model
Taught by
Association for Computing Machinery (ACM)
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent