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Contrastive Clustering Learning for Multi-Behavior Recommendation

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-031-00126-0_11openalex-snapshot

Multi-view Multi-behavior Contrastive Learning in Recommendation

inferredcites →https://doi.org/10.1007/s11263-022-01639-zopenalex-snapshot

Twin Contrastive Learning for Online Clustering

inferredcites →https://doi.org/10.1007/s11280-023-01182-yopenalex-snapshot

Adaptive self-propagation graph convolutional network for recommendation

inferredcites →https://doi.org/10.1016/j.neucom.2018.11.101openalex-snapshot

Cost-sensitive KNN classification

inferredcites →https://doi.org/10.1016/j.neucom.2020.09.094openalex-snapshot

GANLDA: Graph attention network for lncRNA-disease associations prediction

inferredcites →https://doi.org/10.1093/bib/bbab494openalex-snapshot

KGANCDA: predicting circRNA-disease associations based on knowledge graph attention network

inferredcites →https://doi.org/10.1109/iccv48922.2021.00909openalex-snapshot

Graph Contrastive Clustering

inferredcites →https://doi.org/10.1109/icde.2019.00140openalex-snapshot

Neural Multi-task Recommendation from Multi-behavior Data

inferredcites →https://doi.org/10.1109/icde51399.2021.00179openalex-snapshot

Multi-Behavior Enhanced Recommendation with Cross-Interaction Collaborative Relation Modeling

inferredcites →https://doi.org/10.1109/icde53745.2022.00099openalex-snapshot

Contrastive Learning for Sequential Recommendation

inferredcites →https://doi.org/10.1109/tcbb.2024.3387913openalex-snapshot

LGCDA: Predicting CircRNA-Disease Association Based on Fusion of Local and Global Features

inferredcites →https://doi.org/10.1109/tkde.2020.3039463openalex-snapshot

Modelling High-Order Social Relations for Item Recommendation

inferredcites →https://doi.org/10.1109/tkde.2021.3111436openalex-snapshot

Incorporating Link Prediction into Multi-Relational Item Graph Modeling for Session-based Recommendation

inferredcites →https://doi.org/10.1109/tkde.2022.3185149openalex-snapshot

Reachable Distance Function for KNN Classification

inferredcites →https://doi.org/10.1109/tkde.2022.3209008openalex-snapshot

Finding High-quality Item Attributes for Recommendation

inferredcites →https://doi.org/10.1109/tnnls.2023.3260258openalex-snapshot

Multiview Subspace Clustering via Low-Rank Symmetric Affinity Graph

inferredcites →https://doi.org/10.1145/2911451.2911489openalex-snapshot

Fast Matrix Factorization for Online Recommendation with Implicit Feedback

inferredcites →https://doi.org/10.1145/3038912.3052569openalex-snapshot

Neural Collaborative Filtering

inferredcites →https://doi.org/10.1145/3331184.3331199openalex-snapshot

CTRec

inferredcites →https://doi.org/10.1145/3331184.3331267openalex-snapshot

Neural Graph Collaborative Filtering

inferredcites →https://doi.org/10.1145/3340531.3412119openalex-snapshot

Multiplex Graph Neural Networks for Multi-behavior Recommendation

inferredcites →https://doi.org/10.1145/3366423.3380077openalex-snapshot

Beyond Clicks: Modeling Multi-Relational Item Graph for Session-Based Target Behavior Prediction

inferredcites →https://doi.org/10.1145/3373807openalex-snapshot

Efficient Neural Matrix Factorization without Sampling for Recommendation

inferredcites →https://doi.org/10.1145/3397271.3401063openalex-snapshot

LightGCN

inferredcites →https://doi.org/10.1145/3397271.3401072openalex-snapshot

Multi-behavior Recommendation with Graph Convolutional Networks

inferredcites →https://doi.org/10.1145/3404835.3462972openalex-snapshot

Graph Meta Network for Multi-Behavior Recommendation

inferredcites →https://doi.org/10.1145/3442381.3449986openalex-snapshot

Interest-aware Message-Passing GCN for Recommendation

inferredcites →https://doi.org/10.1145/3474085.3475665openalex-snapshot

Contrastive Learning for Cold-Start Recommendation

inferredcites →https://doi.org/10.1145/3477495.3531927openalex-snapshot

A Review-aware Graph Contrastive Learning Framework for Recommendation

inferredcites →https://doi.org/10.1145/3477495.3532009openalex-snapshot

Knowledge Graph Contrastive Learning for Recommendation

inferredcites →https://doi.org/10.1145/3488560.3498527openalex-snapshot

Contrastive Meta Learning with Behavior Multiplicity for Recommendation

inferredcites →https://doi.org/10.1145/3494523openalex-snapshot

A Survey of Machine Learning for Computer Architecture and Systems

inferredcites →https://doi.org/10.1145/3511019openalex-snapshot

KR-GCN: Knowledge-Aware Reasoning with Graph Convolution Network for Explainable Recommendation

inferredcites →https://doi.org/10.1145/3534678.3539342openalex-snapshot

Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation

inferredcites →https://doi.org/10.1145/3535101openalex-snapshot

Graph Neural Networks in Recommender Systems: A Survey

inferredcites →https://doi.org/10.1145/3539597.3570386openalex-snapshot

Knowledge Enhancement for Contrastive Multi-Behavior Recommendation

inferredcites →https://doi.org/10.1145/3539597.3570484openalex-snapshot

Heterogeneous Graph Contrastive Learning for Recommendation

inferredcites →https://doi.org/10.1145/3543507.3583361openalex-snapshot

Debiased Contrastive Learning for Sequential Recommendation

inferredcites →https://doi.org/10.1145/3543507.3583530openalex-snapshot

ApeGNN: Node-Wise Adaptive Aggregation in GNNs for Recommendation

inferredcites →https://doi.org/10.1145/3560487openalex-snapshot

User Cold-Start Recommendation via Inductive Heterogeneous Graph Neural Network

inferredcites →https://doi.org/10.1145/3568022openalex-snapshot

A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions

inferredcites →https://doi.org/10.1145/3604915.3608807openalex-snapshot

Multi-Relational Contrastive Learning for Recommendation

inferredcites →https://doi.org/10.1609/aaai.v34i01.5329openalex-snapshot

Efficient Heterogeneous Collaborative Filtering without Negative Sampling for Recommendation

inferredcites →https://doi.org/10.1609/aaai.v35i10.17037openalex-snapshot

Contrastive Clustering

inferredcites →https://doi.org/10.1609/aaai.v35i5.16515openalex-snapshot

Graph Heterogeneous Multi-Relational Recommendation

inferredcites →https://doi.org/10.1609/aaai.v35i5.16576openalex-snapshot

Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation

inferredcites →https://doi.org/10.1609/aaai.v37i9.26318openalex-snapshot

Substructure Aware Graph Neural Networks

inferredcites →https://doi.org/10.17863/cam.48429openalex-snapshot

Graph Attention Networks

inferredcites →https://doi.org/10.18653/v1/2022.acl-long.352openalex-snapshot

KNN-Contrastive Learning for Out-of-Domain Intent Classification

inferredcites →https://doi.org/10.26599/bdma.2024.9020034openalex-snapshot

Transformer-Based Single-Cell Language Model: A Survey

inferredcites →https://doi.org/10.48550/arxiv.1205.2618openalex-snapshot

BPR: Bayesian Personalized Ranking from Implicit Feedback

inferredcites →https://doi.org/10.48550/arxiv.1702.08720openalex-snapshot

Learning Discrete Representations via Information Maximizing Self-Augmented Training

inferredcites →https://doi.org/10.48550/arxiv.1706.02216openalex-snapshot

Inductive Representation Learning on Large Graphs

inferredcites →https://doi.org/10.48550/arxiv.2101.01317openalex-snapshot

Contrastive Learning for Recommender System

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s00521-026-12227-4openalex-snapshot

AEEMU: Adaptive Ensemble with Enhanced Meta-Learning and signal processing for recommendation systems

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An automated method for precise definition of fracture reduction targets

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Predicting CircRNA-Disease Associations Based on Heterogeneous Graph Neural Network and Knowledge Graph Attribute Mining Attention

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scMSDA: A Novel Multi-View Fusion Framework for Single-Cell RNA-seq Data Clustering with Semantic and Distribution Alignment

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Personalized recommendation methods for e-commerce based on multi-source user behavior data fusion

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Predicting microbe-disease association based on multi-kernel autoencoder and singular value decomposition

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Deep learning for new fashion product demand prediction: integrating visual similarity and demand correction in cold-start scenarios

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A Review on Multi-Types Analysis for Graph Neural Networks-Based Recommendation Systems

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Adaptive fuzzy prototype learning with view-balanced multi-view embeddings for multi-behavior recommendation

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Statistical comparison and uncertainty analysis of graph neural networks and machine learning models for molecular property prediction in drug discovery

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Modeling category and multi-level user intentions for session-based recommendation

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Fuzzy clustering-based dual-channel contrastive learning for multi-behavior recommendation

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Multi-behavioral recommendation algorithm based on decoupled graph convolution

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DCE-MBR: Multi-behavior recommendation via hierarchical denoising and cascade enhancement

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Dual-gated multi-behavior recommendation with variational graph autoencoder

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HCC-MBR: Escaping the quantity-over-quality trap via hierarchical and counterfactual calibration for multi-Behavior recommendation

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Research on multi-behavior recommendation model via relational graph attention networks based on knowledge graph

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Hierarchical knowledge fusion for enhanced health event prediction: Discriminating between frequent and new diseases

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Hierarchical graph contrastive learning with diffusion-enhanced for multi-behavior recommendation

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DiffMBR: diffusion-guided GCN for multi-behavior recommendation

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TASNet: A tri-modal attentive scale robust adaptive fusion framework for progressive mild cognitive impairment classification

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Graph convolutional network with multiple aggregators for learning to branch

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Multi-view clustering with privileged information based on probabilistic tensor factorization

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Interest transfer graph convolutional networks for multi-behavior recommendation

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Knowledge interaction graph attention network for multi-behavior recommendation

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Adaptive reliability-coupled deep semi-NMF with hierarchical dynamic graphs for multi-view clustering

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KG-CNNDTI: a knowledge graph-enhanced prediction model for drug-target interactions and application in virtual screening of natural products against Alzheimer’s disease

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Hither-CMI: Prediction of circRNA-miRNA Interactions Based on a Hybrid Multimodal Network and Higher-Order Neighborhood Information via a Graph Convolutional Network

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MSFCL: Drug Combination Risk Level Prediction Based on Multi-Source Feature Fusion and Contrastive Learning

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MVSL-DSF: Multiview Subspace Representation Learning and Cross-Modal Feature Dynamic Aggregation for Enhanced Drug Side Effect Frequency Prediction

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Path-Based Graph Neural Network for Drug Synergy Prediction and Interpretation

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Multi-Behavior Recommendation System Based on Self-Attention and Contrastive Learning

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Long-Tail Inductive Feature Transfer for Knowledge-Aware Multi-Behavior Recommendation

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