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Cluster-Based Graph Collaborative Filtering
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1109/mc.2009.263openalex-snapshot
Matrix Factorization Techniques for Recommender Systems
inferredcites →https://doi.org/10.1109/tkde.2007.46openalex-snapshot
Random-Walk Computation of Similarities between Nodes of a Graph with Application to Collaborative Recommendation
inferredcites →https://doi.org/10.1109/tkde.2018.2831682openalex-snapshot
NAIS: Neural Attentive Item Similarity Model for Recommendation
inferredcites →https://doi.org/10.1109/tkde.2020.3040772openalex-snapshot
An Attribute-Aware Attentive GCN Model for Attribute Missing in Recommendation
inferredcites →https://doi.org/10.1145/1273496openalex-snapshot
Proceedings of the 24th international conference on Machine learning
inferredcites →https://doi.org/10.1145/1345448.1345465openalex-snapshot
Lessons from the Netflix prize challenge
inferredcites →https://doi.org/10.1145/2835776.2835837openalex-snapshot
Collaborative Denoising Auto-Encoders for Top-N Recommender Systems
inferredcites →https://doi.org/10.1145/3308558.3313493openalex-snapshot
Collaborative Similarity Embedding for Recommender Systems
inferredcites →https://doi.org/10.1145/3331184.3331216openalex-snapshot
A Capsule Network for Recommendation and Explaining What You Like and Dislike
inferredcites →https://doi.org/10.1145/3331184.3331267openalex-snapshot
Neural Graph Collaborative Filtering
inferredcites →https://doi.org/10.1145/3343031.3350953openalex-snapshot
User Diverse Preference Modeling by Multimodal Attentive Metric Learning
inferredcites →https://doi.org/10.1145/3397271.3401137openalex-snapshot
Disentangled Graph Collaborative Filtering
inferredcites →https://doi.org/10.1145/3442381.3449986openalex-snapshot
Interest-aware Message-Passing GCN for Recommendation
inferredcites →https://doi.org/10.1145/3448016.3457240openalex-snapshot
Point-to-Hyperplane Nearest Neighbor Search Beyond the Unit Hypersphere
inferredcites →https://doi.org/10.1145/3477495.3531985openalex-snapshot
Graph Trend Filtering Networks for Recommendation
inferredcites →https://doi.org/10.1145/3485447.3512104openalex-snapshot
Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning
inferredcites →https://doi.org/10.1145/3490478openalex-snapshot
Combining Graph Convolutional Neural Networks and Label Propagation
inferredcites →https://doi.org/10.1145/3523227.3551478openalex-snapshot
Towards Recommender Systems with Community Detection and Quantum Computing
inferredcites →https://doi.org/10.1145/3539618.3591716openalex-snapshot
LightGT: A Light Graph Transformer for Multimedia Recommendation
inferredcites →https://doi.org/10.1145/3543507.3583439openalex-snapshot
Multi-Behavior Recommendation with Cascading Graph Convolution Networks
inferredcites →https://doi.org/10.1145/3555372openalex-snapshot
An Adaptive Graph Pre-training Framework for Localized Collaborative Filtering
inferredcites →https://doi.org/10.1145/3568953openalex-snapshot
Graph Neural Pre-training for Recommendation with Side Information
inferredcites →https://doi.org/10.1145/3617827openalex-snapshot
Dynamic Multimodal Fusion via Meta-Learning Towards Micro-Video Recommendation
inferredcites →https://doi.org/10.1609/aaai.v34i01.5330openalex-snapshot
Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-981-95-3459-3_17openalex-snapshot
Emerging Trends in Knowledge Tracing Models: A Technical Survey from 2022 to 2025
inferred← citeshttps://doi.org/10.1007/s11042-026-21326-2openalex-snapshot
Improving collaborative filtering performance: a comparative analysis of clustering algorithms with and without autoencoders
inferred← citeshttps://doi.org/10.1007/s13042-026-03125-1openalex-snapshot
Learning disentangled multi-intent representations for scalable recommendation
inferred← citeshttps://doi.org/10.1007/s44196-026-01198-yopenalex-snapshot
A Review on Multi-Types Analysis for Graph Neural Networks-Based Recommendation Systems
inferred← citeshttps://doi.org/10.1016/j.engappai.2025.110425openalex-snapshot
Enhancing neighborhood-based co-clustering contrastive learning for multi-entity recommendation
inferred← citeshttps://doi.org/10.1016/j.ipm.2026.104786openalex-snapshot
Disentangled graph recommendation via dynamic long and short-term intent modeling
inferred← citeshttps://doi.org/10.1016/j.knosys.2025.114413openalex-snapshot
Sequential contrastive learning for progressive knowledge tracing
inferred← citeshttps://doi.org/10.1109/tai.2026.3665848openalex-snapshot
GT-EBRB: An Extended Belief Rule Base System Optimized via Clustering Graph Structure and Graph Transformer
inferred← citeshttps://doi.org/10.1109/tnse.2025.3609971openalex-snapshot
Enhancing Recommendation Performance Using Attribute-Aware Message-Passing and Augmentation GCN
inferred← citeshttps://doi.org/10.1145/3696410.3714843openalex-snapshot
Personalized Image Generation with Large Multimodal Models
inferred← citeshttps://doi.org/10.1145/3704999openalex-snapshot
Understanding Before Recommendation: Semantic Aspect-Aware Review Exploitation via Large Language Models
inferred← citeshttps://doi.org/10.1145/3728464openalex-snapshot
PolyCF: Towards Optimal Spectral Graph Filters for Collaborative Filtering
inferred← citeshttps://doi.org/10.1186/s13677-026-00890-wopenalex-snapshot
Excessive alignment hinders representation learning in cloud-scale collaborative filtering
inferred← citeshttps://doi.org/10.32604/cmc.2025.066382openalex-snapshot
DMGNN: A Dual Multi-Relational GNN Model for Enhanced Recommendation
inferred← citeshttps://doi.org/10.3390/app15041961openalex-snapshot
Prototypical Graph Contrastive Learning for Recommendation
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