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Multimedia recommendation
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Modality-Balanced Learning for Multimedia Recommendation
It is Never Too Late to Mend: Separate Learning for Multimedia Recommendation
BeFA: A General Behavior-driven Feature Adapter for Multimedia Recommendation
MONET: Modality-Embracing Graph Convolutional Network and Target-Aware Attention for Multimedia Recommendation
LD4MRec: Simplifying and Powering Diffusion Model for Multimedia Recommendation
Formalizing Multimedia Recommendation through Multimodal Deep Learning
Pareto Invariant Representation Learning for Multimedia Recommendation
Multi-View Graph Convolutional Network for Multimedia Recommendation
News Popularity Beyond the Click-Through-Rate for Personalized Recommendations
Cross-Modal Content Inference and Feature Enrichment for Cold-Start Recommendation
Mining Stable Preferences: Adaptive Modality Decorrelation for Multimedia Recommendation
Multi-Modal Self-Supervised Learning for Recommendation
Self-Supervised Learning for Multimedia Recommendation
A multimedia recommendation model based on collaborative graph
DualGNN: Dual Graph Neural Network for Multimedia Recommendation
GRCN: Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback
Latent Structure Mining with Contrastive Modality Fusion for Multimedia Recommendation
Mining Latent Structures for Multimedia Recommendation
ContentWise Impressions: An Industrial Dataset with Impressions Included
Fast Non-Local Neural Networks with Spectral Residual Learning
SMP Challenge: An Overview of Social Media Prediction Challenge 2019
Food Recommendation: Framework, Existing Solutions and Challenges
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.