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Found 3 papers, 2 papers with code
GRCN: Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback
Reorganizing implicit feedback of users as a user-item interaction graph facilitates the applications of graph convolutional networks (GCNs) in recommendation tasks.
Hierarchical User Intent Graph Network forMultimedia Recommendation
In this work, we aim to learn multi-level user intents from the co-interacted patterns of items, so as to obtain high-quality representations of users and items and further enhance the recommendation performance.
Sampler Design for Bayesian Personalized Ranking by Leveraging View Data
First, we find that sampling negative items from the whole space is unnecessary and may even degrade the performance.
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