Copertina

SynerGraph: An Integrated Graph Convolution Network for Multimodal Recommendation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Burabak, Mert, Aytekin, Tevfik
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Information Retrieval
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

COHESION: Composite Graph Convolutional Network with Dual-Stage Fusion for Multimodal Recommendation
di: Xu, Jinfeng, et al.
Pubblicazione: (2025)

Beyond Graph Convolution: Multimodal Recommendation with Topology-aware MLPs
di: Huang, Junjie, et al.
Pubblicazione: (2024)

Spectrum-based Modality Representation Fusion Graph Convolutional Network for Multimodal Recommendation
di: Ong, Rongqing Kenneth, et al.
Pubblicazione: (2024)

The Best is Yet to Come: Graph Convolution in the Testing Phase for Multimodal Recommendation
di: Xu, Jinfeng, et al.
Pubblicazione: (2025)

HGCH: A Hyperbolic Graph Convolution Network Model for Heterogeneous Collaborative Graph Recommendation
di: Zhang, Lu, et al.
Pubblicazione: (2023)

Disentangled Cascaded Graph Convolution Networks for Multi-Behavior Recommendation
di: Cheng, Zhiyong, et al.
Pubblicazione: (2024)

Lossless and Privacy-Preserving Graph Convolution Network for Federated Item Recommendation
di: Wu, Guowei, et al.
Pubblicazione: (2024)

SWGCN: Synergy Weighted Graph Convolutional Network for Multi-Behavior Recommendation
di: Chen, Fangda, et al.
Pubblicazione: (2026)

IA-GCN: Interactive Graph Convolutional Network for Recommendation
di: Zhang, Yinan, et al.
Pubblicazione: (2022)

Don't Lose Yourself: Boosting Multimodal Recommendation via Reducing Node-neighbor Discrepancy in Graph Convolutional Network
di: Chen, Zheyu, et al.
Pubblicazione: (2024)

HEC-GCN: Hypergraph Enhanced Cascading Graph Convolution Network for Multi-Behavior Recommendation
di: Yin, Yabo, et al.
Pubblicazione: (2024)

Non-parametric Graph Convolution for Re-ranking in Recommendation Systems
di: Ouyang, Zhongyu, et al.
Pubblicazione: (2025)

Heterophily-Aware Fair Recommendation using Graph Convolutional Networks
di: Gholinejad, Nemat, et al.
Pubblicazione: (2024)

Ripple Knowledge Graph Convolutional Networks For Recommendation Systems
di: Li, Chen, et al.
Pubblicazione: (2023)

LGMRec: Local and Global Graph Learning for Multimodal Recommendation
di: Guo, Zhiqiang, et al.
Pubblicazione: (2023)

Adaptive Graph Integration for Cross-Domain Recommendation via Heterogeneous Graph Coordinators
di: Zhang, Hengyu, et al.
Pubblicazione: (2024)

Graph Cross-Correlated Network for Recommendation
di: Chen, Hao, et al.
Pubblicazione: (2024)

Distance-aware Self-adaptive Graph Convolution for Fine-grained Hierarchical Recommendation
di: Huang, Tao, et al.
Pubblicazione: (2025)

IGDMRec: Behavior Conditioned Item Graph Diffusion for Multimodal Recommendation
di: Guo, Ziyuan, et al.
Pubblicazione: (2025)

Combining social relations and interaction data in Recommender System with Graph Convolution Collaborative Filtering
di: Tran, Tin T., et al.
Pubblicazione: (2025)

Cross-Modal Attention Network with Dual Graph Learning in Multimodal Recommendation
di: Dai, Ji, et al.
Pubblicazione: (2026)

MLLMRec: A Preference Reasoning Paradigm with Graph Refinement for Multimodal Recommendation
di: Dang, Yuzhuo, et al.
Pubblicazione: (2025)

Training-free Graph-based Imputation of Missing Modalities in Multimodal Recommendation
di: Malitesta, Daniele, et al.
Pubblicazione: (2026)

Multi-behavior Recommendation with SVD Graph Neural Networks
di: Fu, Shengxi, et al.
Pubblicazione: (2023)

Gated Multimodal Graph Learning for Personalized Recommendation
di: Liu, Sibei, et al.
Pubblicazione: (2025)

Structurally Refined Graph Transformer for Multimodal Recommendation
di: Shi, Ke, et al.
Pubblicazione: (2025)

Sequences as Nodes for Contrastive Multimodal Graph Recommendation
di: Sahyouni, Bucher, et al.
Pubblicazione: (2026)

Integrating Structure-Aware Attention and Knowledge Graphs in Explainable Recommendation Systems
di: Lyu, Shuangquan, et al.
Pubblicazione: (2025)

Multi-Behavior Collaborative Filtering with Partial Order Graph Convolutional Networks
di: Zhang, Yijie, et al.
Pubblicazione: (2024)

Disentangled Graph Variational Auto-Encoder for Multimodal Recommendation with Interpretability
di: Zhou, Xin, et al.
Pubblicazione: (2024)

Context-Adaptive Graph Neural Networks for Next POI Recommendation
di: Lei, Yu, et al.
Pubblicazione: (2025)

Robust Multimodal Recommendation via Graph Retrieval-Enhanced Modality Completion
di: Li, Yuan, et al.
Pubblicazione: (2026)

Graph Bottlenecked Social Recommendation
di: Yang, Yonghui, et al.
Pubblicazione: (2024)

Multimodal Graph Neural Network for Recommendation with Dynamic De-redundancy and Modality-Guided Feature De-noisy
di: Mo, Feng, et al.
Pubblicazione: (2024)

Semantic Item Graph Enhancement for Multimodal Recommendation
di: Zhang, Xiaoxiong, et al.
Pubblicazione: (2025)

Macro Graph Neural Networks for Online Billion-Scale Recommender Systems
di: Chen, Hao, et al.
Pubblicazione: (2024)

Graph and Sequential Neural Networks in Session-based Recommendation: A Survey
di: Li, Zihao, et al.
Pubblicazione: (2024)

On the Impact of Graph Neural Networks in Recommender Systems: A Topological Perspective
di: Malitesta, Daniele, et al.
Pubblicazione: (2025)

Graph Neural Network for Product Recommendation on the Amazon Co-purchase Graph
di: Cao, Mengyang, et al.
Pubblicazione: (2025)

Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation
di: Zhang, Weizhi, et al.
Pubblicazione: (2024)