Multimodality invariant learning for multimedia-based new item recommendation
Multimedia-based recommendation provides personalized item suggestions by learning the
content preferences of users. With the proliferation of digital devices and APPs, a huge …
content preferences of users. With the proliferation of digital devices and APPs, a huge …
[HTML][HTML] Reinforcement learning for addressing the cold-user problem in recommender systems
Recommender systems are widely used in webshops because of their ability to provide
users with personalized recommendations. However, the cold-user problem (ie …
users with personalized recommendations. However, the cold-user problem (ie …
Content-based graph reconstruction for cold-start item recommendation
J Kim, E Kim, K Yeo, Y Jeon, C Kim, S Lee… - Proceedings of the 47th …, 2024 - dl.acm.org
Graph convolutions have been successfully applied to recommendation systems, utilizing
high-order collaborative signals present in the user-item interaction graph. This idea …
high-order collaborative signals present in the user-item interaction graph. This idea …
Cold-Start Recommendation towards the Era of Large Language Models (LLMs): A Comprehensive Survey and Roadmap
W Zhang, Y Bei, L Yang, HP Zou, P Zhou, A Liu… - ar** Matters: An Unsupervised Alignment enhanced Cross-Domain Cold-Start Recommendation
Cold-start recommendation is a long-standing challenge when presenting potential
preferred items to new users. Most empirical studies leverage side information to promote …
preferred items to new users. Most empirical studies leverage side information to promote …
Teaching content recommendations in music appreciation courses via graph embedding learning
The traditional music appreciation course teaching model relies on questionnaires or
manual decision-making to determine teaching content, which is time-consuming and easily …
manual decision-making to determine teaching content, which is time-consuming and easily …
Data Augmentation using Reverse Prompt for Cost-Efficient Cold-Start Recommendation
G Kusano - Proceedings of the 18th ACM Conference on …, 2024 - dl.acm.org
Recommendation systems that use auxiliary information such as product names and
categories have been proposed to address the cold-start problem. However, these methods …
categories have been proposed to address the cold-start problem. However, these methods …
When SparseMoE Meets Noisy Interactions: An Ensemble View on Denoising Recommendation
Learning user preferences from implicit feedback is one of the core challenges in
recommendation. The difficulty lies in the potential noise within implicit feedback. Therefore …
recommendation. The difficulty lies in the potential noise within implicit feedback. Therefore …