In our work, we propose to obtain embeddings by using the neighborhood propagation mechanism on two coupled graph neural networks, i.e., user-item interaction ...
Inspired by this, the represen- tation learning methods based on graph convolutional network are more modeled from the perspective of adaptive neighbor.
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What is the difference between GCN and graph attention networks?
What are graph convolutional networks used for?
Why graph neural networks for recommender systems?
What is graph attention network used for?
A new social recommendation framework with hierarchical attention, i.e., neighbor-level and graph-level attention) Attentional Social Recommendation system ...
In this paper, we proposed a graph-based recommendation algorithm, GARec, as a Graph Neural Network which applies spatial graph convolutional neural network ...
Missing: Attentional | Show results with:Attentional
Oct 27, 2022 · In this blog, we will discuss how we can leverage Graph Neural Networks for Social Recommendation. Especially we will discuss a framework ...
Missing: Attentional | Show results with:Attentional
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Aug 18, 2021 · Existing recommendation system studies based on graph convolutional networks have achieved great success, but they focus more on the bipartite ...
Specifically, in the SIL module, we arrange social graphs in a sequential order and borrow the power of graph convolution networks (GCNs) to learn social ...
Mar 11, 2024 · Finally, the attention mechanism is used to learn the potential factors of users and projects. Experiments on two real recommendation system ...
Missing: Attentional | Show results with:Attentional
Dec 8, 2022 · For this reason, SocialRS has increasingly attracted attention. In particular, with the advance of graph neural networks (GNN), many GNN-based ...
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Mar 21, 2023 · To address this problem, in this paper we propose a graph neural network social recommendation algorithm integrating multi-head attention ...