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Found 5 papers, 2 papers with code
Instant Representation Learning for Recommendation over Large Dynamic Graphs
Furthermore, the Neighborhood Disturbance existing in dynamic graphs deteriorates the performance of neighbor-aggregation based graph models.
Multi-behavior Self-supervised Learning for Recommendation
Secondly, existing methods utilizing self-supervised learning (SSL) to tackle the data sparsity neglect the serious optimization imbalance between the SSL task and the target task.
HybridGNN: Learning Hybrid Representation in Multiplex Heterogeneous Networks
One of the most important tasks in recommender systems is to predict the potential connection between two nodes under a specific edge type (i. e., relationship).
Concept-Aware Denoising Graph Neural Network for Micro-Video Recommendation
In this paper, we propose a novel concept-aware denoising graph neural network (named CONDE) for micro-video recommendation.
Expanding Semantic Knowledge for Zero-shot Graph Embedding
Zero-shot graph embedding is a major challenge for supervised graph learning.
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