A Deep Graph Neural Network-Based Mechanism for Social Recommendations. Z. Guo, and H. Wang. IEEE Trans. Ind. Informatics, 17 (4): 2776-2783 (2021 ).
Feb 19, 2019 · Title:Graph Neural Networks for Social Recommendation ; Subjects: Information Retrieval (cs.IR); Machine Learning (cs.LG); Social and Information ...
Missing: Deep Mechanism
Recent developments of the Graph Neural Networks (GNNs) also provide recommender systems (RSs) with powerful backbones to learn embeddings from a user-item ...
[P] Training a Simple Transformer Neural Net on Conway's Game ... Or would an architecture based on a recurrent network or transformer be more appropriate?
Sep 7, 2023 · Graph Neural Network (GNN) could handle the topological structure information of the graph and derive high-level representations of nodes in the ...
To address the social recommendation problem, the authors of [42] propose a GNN-based framework able to coherently model graph data with the aim to learn better ...
This paper provides a principled approach to jointly capture interactions and opinions in the user-item graph and proposes the framework GraphRec, ...
In this survey, we conduct a comprehensive review of the literature on graph neural network-based recommender systems. We first introduce the background and the ...
Social recommendation · Tripartite Heterogeneous Graph Propagation for Large-scale Social Recommendation (2019) [doc] · Graph Neural Networks for Social ...
Sep 11, 2023 · Graph Neural Networks (GNNs) are a class of deep learning methods designed to perform inference on data described by graphs.