Changes
On December 16, 2024 at 6:47:38 PM UTC, admin:
-
Changed value of field
doi_date_published
to2024-12-16
in Mixed Supervised Graph Contrastive Learning for Recommendation -
Changed value of field
doi_status
toTrue
in Mixed Supervised Graph Contrastive Learning for Recommendation -
Added resource Original Metadata to Mixed Supervised Graph Contrastive Learning for Recommendation
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3 | "author": "Weizhi Zhang", | 3 | "author": "Weizhi Zhang", | ||
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15 | "extra_author": "Liangwei Yang", | 15 | "extra_author": "Liangwei Yang", | ||
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19 | "extra_author": "Zihe Song", | 19 | "extra_author": "Zihe Song", | ||
20 | "orcid": "" | 20 | "orcid": "" | ||
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23 | "extra_author": "Henry Peng Zou", | 23 | "extra_author": "Henry Peng Zou", | ||
24 | "orcid": "" | 24 | "orcid": "" | ||
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56 | "name": | 56 | "name": | ||
57 | "mixed-supervised-graph-contrastive-learning-for-recommendation", | 57 | "mixed-supervised-graph-contrastive-learning-for-recommendation", | ||
58 | "notes": "Recommender systems (RecSys) play a vital role in online | 58 | "notes": "Recommender systems (RecSys) play a vital role in online | ||
59 | platforms, offering users personalized suggestions amidst vast | 59 | platforms, offering users personalized suggestions amidst vast | ||
60 | information. Graph contrastive learning aims to learn from high-order | 60 | information. Graph contrastive learning aims to learn from high-order | ||
61 | collaborative filtering signals with unsupervised augmentation on the | 61 | collaborative filtering signals with unsupervised augmentation on the | ||
62 | user-item bipartite graph, which predominantly relies on the | 62 | user-item bipartite graph, which predominantly relies on the | ||
63 | multi-task learning framework involving both the pair-wise | 63 | multi-task learning framework involving both the pair-wise | ||
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110 | Recommendation", | 151 | Recommendation", | ||
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