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Enhancing Matrix Factorization-based Recommender Systems via Graph ...
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Therefore, this work introduces the graph neural networks to enhance matrix factorization-based recommender systems. And the proposal in this work is named GNN- ...
Enhancing Matrix Factorization-based. Recommender Systems via Graph Neural Networks. 1st Zhiwei Guo. School of Computer Science and. Engineering. Chongqing ...
Therefore, this work introduces the graph neural networks to enhance matrix factorization-based recommender systems. And the proposal in this work is named GNN- ...
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Feb 21, 2024 · In this paper, we propose a Linear-Time Graph Neural Network (LTGNN) to scale up GNN-based recommender systems to achieve comparable scalability ...
Mar 31, 2021 · This post covers a research project conducted with Decathlon Canada regarding recommendation using Graph Neural Networks.
Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion. KDD, 2020. Wenqiang et al. Interactive Path Reasoning on Graph for ...
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Feb 9, 2024 · We demonstrate that our approach can improve accuracy compared to matrix factorization and neural network (NN)-based recommender systems.
Though, CF methods still suffer from cold start and data sparsity. This paper proposes an improved hybrid-based RS, namely Neural Matrix Factorization++ (NeuMF ...
Jun 20, 2022 · Following this line of research, several deep learning based matrix factorization ... Matrix factorization techniques for recommender systems.