Multi-interaction fusion collaborative filtering for social recommendation
Abstract GNNs (Graph Neural Networks) use graph structure to make recommendations,
receiving more and more attention. Firstly, existing work focuses on aggregating social …
receiving more and more attention. Firstly, existing work focuses on aggregating social …
Collaborative filtering with social exposure: A modular approach to social recommendation
This paper is concerned with how to make efficient use of social information to improve
recommendations. Most existing social recommender systems assume people share similar …
recommendations. Most existing social recommender systems assume people share similar …
GDSRec: Graph-based decentralized collaborative filtering for social recommendation
Generating recommendations based on user-item interactions and user-user social relations
is a common use case in web-based systems. These connections can be naturally …
is a common use case in web-based systems. These connections can be naturally …
Deep social collaborative filtering
Recommender systems are crucial to alleviate the information overload problem in online
worlds. Most of the modern recommender systems capture users' preference towards items …
worlds. Most of the modern recommender systems capture users' preference towards items …
Social recommendation via deep neural network-based multi-task learning
Recent years are witnessing the rapid development of social recommendation to improve
the performance of recommender system, especially for cold start problem. Many of the …
the performance of recommender system, especially for cold start problem. Many of the …
User-Context Collaboration and Tensor Factorization for GNN-Based Social Recommendation
W Wang, Z Quan, S Zhao, G Sun, Y Li… - … on Network Science …, 2023 - ieeexplore.ieee.org
One goal of social recommendation is to utilize social information to alleviate data sparsity
and improve recommendation accuracy. User social relationships are inherently graph …
and improve recommendation accuracy. User social relationships are inherently graph …
Social collaborative filtering ensemble
Collaborative filtering (CF) technique plays an important role in generating personalized
recommendations, but its performance is challenged by the problems of data sparsity and …
recommendations, but its performance is challenged by the problems of data sparsity and …
Graph neural networks for preference social recommendation
GF Ma, XH Yang, Y Tong, Y Zhou - PeerJ Computer Science, 2023 - peerj.com
Social recommendation aims to improve the performance of recommendation systems with
additional social network information. In the state of art, there are two major problems in …
additional social network information. In the state of art, there are two major problems in …
A community-based collaborative filtering method for social recommender systems
Recommender systems have become indispensable for recommending items of interest to
users and have been successfully deployed in a wide range of real-world applications. In …
users and have been successfully deployed in a wide range of real-world applications. In …
Cold-start recommendation using bi-clustering and fusion for large-scale social recommender systems
Social recommender systems leverage collaborative filtering (CF) to serve users with
content that is of potential interesting to active users. A wide spectrum of CF schemes has …
content that is of potential interesting to active users. A wide spectrum of CF schemes has …