VideoRecSys + LargeRecSys 2024

Abstract

With the exponential growth of video and other content across various domains including entertainment, e-commerce, education and social media, there is a growing need for personalized content recommendations that are relevant to users’ interests. However, building effective and scalable content recommender systems is challenging due to factors such as the vast volume of content, diversity of user preferences, inherent noise and bias in data, and the need for real-time recommendations. The VideoRecSys + LargeRecSys joint workshop aims to bring together researchers, practitioners and industry experts to discuss the latest trends, challenges and opportunities in large-scale content recommendation systems. It will provide a forum for participants to delve into nuanced topics critical to advancing large-scale content recommendations, including the use of modern innovations like large language models (LLMs) to enhance personalization and efficiency. The workshop also aims to foster collaboration within the growing video recommender systems community and inspire fresh avenues of applied research in this rapidly evolving domain [5, 7]. This workshop will feature multiple domain experts from industry and academia leading discussions about their work on large-scale recommender systems. In addition to speaker-led sessions, the workshop will include a space for the RecSys community to contribute their own research and findings on developing recommender systems solutions at scale.