稀少
发表于 2025-3-21 19:49:21
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CLIFF
发表于 2025-3-21 22:48:44
Hierarchical Review-Based Recommendation with Contrastive Collaborational gated sentiment-aware model for rating prediction in this paper. Specifically, to automatically suppress the influence of noisy reviews, we propose a hierarchical gating network to select informative textual signals at different levels of granularity. Specifically, a local gating module is propos
相信
发表于 2025-3-22 03:40:21
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香料
发表于 2025-3-22 07:56:15
Adaptive Augmentation and Neighbor Contrastive Learning for Multi-Behavior Recommendation Edge weights are neglected when constructing augmented views based on the interaction graph. It leads to the omission of crucial nodes or edges during the augmentation process. (2) During contrastive learning, positive pairs are adopted by using topology structure. However, we argue that semantic s
FLORA
发表于 2025-3-22 11:28:09
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Commemorate
发表于 2025-3-22 14:16:02
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无能性
发表于 2025-3-22 17:36:37
Contrastive Generator Generative Adversarial Networks for Sequential Recommendationon their historical interactions. However, these methods have some drawbacks as they require an effective generative model and training procedure to produce satisfactory results. These disadvantages include: 1) generative models lacking better generators for generative item sequences that user may b
coalition
发表于 2025-3-22 21:34:08
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GLARE
发表于 2025-3-23 02:40:50
Distribution-Aware Diversification for Personalized Re-ranking in Recommendationking stage, as the final stage of the recommendation system, has a direct impact on the recommendation results. Many works dedicate to improving the diversity of recommendation systems in the re-ranking stage, but most of them optimize diversity based on traditional pairwise distance between element
Directed
发表于 2025-3-23 06:26:45
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