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Kan-Infused Social Recommendation: A Contrastive Graph Learning Approach with Bidirectional Feature Fusion

https://doi.org/10.2139/ssrn.5138296
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Outgoing claims: the papers this work cites, builds on, or argues with.

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SARWAS: Deep ensemble learning techniques for sentiment based recommendation system
inferredcites →https://doi.org/10.1016/j.ipm.2023.103353openalex-snapshot
Meta-relation assisted knowledge-aware coupled graph neural network for recommendation
inferredcites →https://doi.org/10.1016/j.knosys.2022.108921openalex-snapshot
Integrating User-Group relationships under interest similarity constraints for social recommendation
inferredcites →https://doi.org/10.1016/j.neucom.2022.09.102openalex-snapshot
Motifs-based recommender system via hypergraph convolution and contrastive learning
inferredcites →https://doi.org/10.1109/icde55515.2023.00180openalex-snapshot
Disentangled Graph Social Recommendation
inferredcites →https://doi.org/10.1109/mc.2009.263openalex-snapshot
Matrix Factorization Techniques for Recommender Systems
inferredcites →https://doi.org/10.1109/msp.2017.2693418openalex-snapshot
Geometric Deep Learning: Going beyond Euclidean data
inferredcites →https://doi.org/10.1109/tkde.2020.3048414openalex-snapshot
DiffNet++: A Neural Influence and Interest Diffusion Network for Social Recommendation
inferredcites →https://doi.org/10.1109/tkde.2022.3185388openalex-snapshot
Disentangled Modeling of Social Homophily and Influence for Social Recommendation
inferredcites →https://doi.org/10.1109/tkde.2023.3288135openalex-snapshot
XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation
inferredcites →https://doi.org/10.1109/tsmc.2023.3242308openalex-snapshot
Graph-Augmented Co-Attention Model for Socio-Sequential Recommendation
inferredcites →https://doi.org/10.1145/3038912.3052569openalex-snapshot
Neural Collaborative Filtering
inferredcites →https://doi.org/10.1145/3308558.3313442openalex-snapshot
Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems
inferredcites →https://doi.org/10.1145/3308558.3313488openalex-snapshot
Graph Neural Networks for Social Recommendation
inferredcites →https://doi.org/10.1145/3331184.3331214openalex-snapshot
A Neural Influence Diffusion Model for Social Recommendation
inferredcites →https://doi.org/10.1145/3459637.3482480openalex-snapshot
Social Recommendation with Self-Supervised Metagraph Informax Network
inferredcites →https://doi.org/10.1145/3485447.3512003openalex-snapshot
Revisiting Graph based Social Recommendation: A Distillation Enhanced Social Graph Network
inferredcites →https://doi.org/10.1145/3533725openalex-snapshot
Be Causal: De-Biasing Social Network Confounding in Recommendation
inferredcites →https://doi.org/10.1145/3543507.3583374openalex-snapshot
Robust Preference-Guided Denoising for Graph based Social Recommendation
inferredcites →https://doi.org/10.1145/3580305.3599400openalex-snapshot
Knowledge Graph Self-Supervised Rationalization for Recommendation
inferredcites →https://doi.org/10.1145/3616855.3635784openalex-snapshot
MADM: A Model-agnostic Denoising Module for Graph-based Social Recommendation
inferredcites →https://doi.org/10.1145/3626772.3657696openalex-snapshot
Behavior-Contextualized Item Preference Modeling for Multi-Behavior Recommendation
inferredcites →https://doi.org/10.1145/3696417openalex-snapshot
Multi-Behavior Recommendation with Personalized Directed Acyclic Behavior Graphs
inferredcites →https://doi.org/10.13025/15118openalex-snapshot
SoRec: Social recommendation using probabilistic matrix factorization
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.v34i01.5330openalex-snapshot
Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach
inferredcites →https://doi.org/10.48550/arxiv.1609.02907openalex-snapshot
Semi-Supervised Classification with Graph Convolutional Networks
inferredcites →https://doi.org/10.48550/arxiv.2002.02126openalex-snapshot
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
inferredcites →https://doi.org/10.48550/arxiv.2112.08679openalex-snapshot
Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendation
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