Dec 25, 2023 · Abstract: Learning high-quality representations of users, items, and tags from historical interactive data is crucial for personalized tag ...
Jan 25, 2024 · In order to further improve the quality of representation learning for PTR, the paper proposes a personalized tag recommendation model based on ...
ABSTRACT Learning high-quality representations of users, items, and tags from historical interactive data is crucial for personalized tag recommendation ...
Jan 3, 2024 · Existing hyperbolic embedding-based tag recommendation models only account for the macro properties of the data, overlooking the node-level ...
Jan 1, 2024 · Zhang C. et al. A Graph Neural Networks-Based Learning Framework With Hyperbolic Embedding for Personalized Tag Recommendation // IEEE Access.
This article proposes a graph neural networks boosted personalized tag recommendation model, namely NGTR, which integrates thegraph neural networks into the ...
Dec 25, 2023 · A Graph Neural Networks-Based Learning Framework With Hyperbolic Embedding for Personalized Tag Recommendation · IEEE Access ( IF 3.9 ) Pub ...
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A Graph Neural Networks-Based Learning Framework With Hyperbolic Embedding for Personalized Tag Recommendation. IEEE Access. 2024 | Journal article.
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Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications - GitHub ...
Apr 11, 2022 · Personalized Tag Recommendation (PTR) aims to automatically generate a list of tags for users to annotate web resources, the so-called items ...