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Found 3 papers, 3 papers with code
NFARec: A Negative Feedback-Aware Recommender Model
In this paper, we propose a negative feedback-aware recommender model (NFARec) that maximizes the leverage of negative feedback.
CaDRec: Contextualized and Debiased Recommender Model
To tackle the skewed distribution, we propose two strategies for disentangling interactions: (1) modeling individual biases to learn unbiased item embeddings, and (2) incorporating item popularity with positional encoding.
TLSAN: Time-aware Long- and Short-term Attention Network for Next-item Recommendation
Especially, the attention mechanism in deep learning enables recommender systems to incorporate various features in an adaptive way.
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