[HTML][HTML] Beyond-accuracy: a review on diversity, serendipity, and fairness in recommender systems based on graph neural networks
By providing personalized suggestions to users, recommender systems have become
essential to numerous online platforms. Collaborative filtering, particularly graph-based …
essential to numerous online platforms. Collaborative filtering, particularly graph-based …
Analysis of Recommender System Using Generative Artificial Intelligence: A Systematic Literature Review
Recommender Systems (RSs), which generate personalized content, have become a
technological tool with diverse applications for users. While numerous RSs have been …
technological tool with diverse applications for users. While numerous RSs have been …
[HTML][HTML] Bias assessment approaches for addressing user-centered fairness in GNN-based recommender systems
In today's technology-driven society, many decisions are made based on the results
provided by machine learning algorithms. It is widely known that the models generated by …
provided by machine learning algorithms. It is widely known that the models generated by …
Joint item recommendation and trust prediction with graph neural networks
G Wang, H Wang, J Gong, J Ma - Knowledge-Based Systems, 2024 - Elsevier
Item recommendation and trust prediction are desired by users on social network platforms
since they can help users find their favourite items or friends faster. Existing methods usually …
since they can help users find their favourite items or friends faster. Existing methods usually …
Mitigating Exposure Bias in Recommender Systems–A Comparative Analysis of Discrete Choice Models
When implicit feedback recommender systems expose users to items, they influence the
users' choices and, consequently, their own future recommendations. This effect is known as …
users' choices and, consequently, their own future recommendations. This effect is known as …
[HTML][HTML] Social Network Community Detection to Deal with Gray-Sheep and Cold-Start Problems in Music Recommender Systems
D Sánchez-Moreno, VF López Batista… - Information, 2024 - mdpi.com
Information from social networks is currently being widely used in many application
domains, although in the music recommendation area, its use is less common because of …
domains, although in the music recommendation area, its use is less common because of …
Deep Learning-Based Recommendation System: Systematic Review and Classification
In recent years, recommendation systems have become essential for businesses to enhance
customer satisfaction and generate revenue in various domains, such as e-commerce and …
customer satisfaction and generate revenue in various domains, such as e-commerce and …
Effects of the spiral of silence on minority groups in recommender systems
SN Khan, E Herder - Proceedings of the 34th ACM Conference on …, 2023 - dl.acm.org
Recommender systems play a critical role in today's data-rich landscape, where the
abundance of information necessitates their ability to present the most relevant choices for …
abundance of information necessitates their ability to present the most relevant choices for …
[HTML][HTML] Multi-Level Knowledge-Aware Contrastive Learning Network for Personalized Recipe Recommendation
Z Bai, Y Huang, S Zhang, P Li, Y Chang, X Lin - Applied Sciences, 2022 - mdpi.com
Personalized recipe recommendation is attracting more and more attention, which can help
people make choices from the exploding growth of online food information. Unlike other …
people make choices from the exploding growth of online food information. Unlike other …
[PDF][PDF] Quantifying Fairness Disparities in Graph-Based Neural Network Recommender Systems for Protected Groups.
The wide acceptance of Recommender Systems (RS) among users for product and service
suggestions has led to the proposal of multiple recommendation methods that have …
suggestions has led to the proposal of multiple recommendation methods that have …