Nov 1, 2022 · This paper explores and verifies the disadvantages of directly constructing contrastive learning tasks on different channels with practical ...
This paper explores and verifies the disadvantages of directly constructing contrastive learning tasks on different channels with practical experiments and ...
Sep 2, 2021 · Under such circumstances, this paper explores and verifies the deficiency of directly constructing contrastive learning tasks on different ...
A comprehensive and systematic review of the literature on GNN-based SocialRS methods and proposes a novel taxonomy, which classifies the GNN-based SocialRS ...
Motifs-Res. the Demo code of paper "Motifs-based Recommender System via Hypergraph Convolution and Contrastive Learning". If you find code useful, pllease ...
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Sep 21, 2022 · Recently, the strategy of leveraging various motifs to model social semantic information and using self-supervised learning tasks to boost ...
Apr 27, 2024 · To address these challenges, in this article, we propose a novel method DH-HGCN++ for multiple social recommendations. Specifically, dual ...
Sep 26, 2023 · To address these issues, this paper proposes a multi-channel hypergraph convolutional network model based on contrastive learning, aiming to ...
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Mar 30, 2024 · Experiment results demonstrate that our proposed method consistently outperforms the state-of-the-art baselines on Top-N recommendations.
Then by maximizing the mutual information between the session representations learned via the two channels through contrastive learning, the recommendation ...
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