SOTAVerified

Recommendation Systems

Recommendation System in AI Research

A Recommendation System is a specialized AI-driven model that analyzes user preferences and behaviors to suggest relevant content, products, or services. It is widely used in domains like e-commerce, streaming platforms, social media, and personalized learning.

AI research in recommendation systems focuses on:

  • Collaborative Filtering: Predicting user preferences based on similar users' choices.
  • Content-Based Filtering: Recommending items based on user history and item characteristics.
  • Hybrid Models: Combining multiple techniques for better accuracy.
  • Deep Learning & Transformers: Using neural networks and self-attention mechanisms for personalized recommendations.
  • Graph-Based Approaches: Leveraging knowledge graphs for relationship-aware recommendations.

Key challenges include data sparsity, scalability, and bias mitigation. Cutting-edge research explores reinforcement learning, explainability, and privacy-preserving methods to enhance recommendation systems.

Papers

Showing 28012850 of 6047 papers

TitleStatusHype
Topic-Centric Explanations for News RecommendationCode0
NFTs to MARS: Multi-Attention Recommender System for NFTs0
Interpolating Item and User Fairness in Multi-Sided Recommendations0
Enhancing Topic Extraction in Recommender Systems with Entropy Regularization0
Securing Visually-Aware Recommender Systems: An Adversarial Image Reconstruction and Detection Framework0
Mean-Variance Efficient Collaborative Filtering for Stock Recommendation0
Skellam Rank: Fair Learning to Rank Algorithm Based on Poisson Process and Skellam Distribution for Recommender Systems0
Spectral gap-based deterministic tensor completion0
Bayesian Knowledge-driven Critiquing with Indirect Evidence0
Knowledge Enhanced Multi-Domain Recommendations in an AI Assistant Application0
Interactive Explanation with Varying Level of Details in an Explainable Scientific Literature Recommender System0
COURIER: Contrastive User Intention Reconstruction for Large-Scale Visual RecommendationCode0
Safe Collaborative FilteringCode0
Vague Preference Policy Learning for Conversational Recommendation0
XInsight: Revealing Model Insights for GNNs with Flow-based Explanations0
PANE-GNN: Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation0
Constraint-based recommender system for crisis management simulations0
Set-to-Sequence Ranking-based Concept-aware Learning Path Recommendation0
Answering Compositional Queries with Set-Theoretic Embeddings0
Tree based Progressive Regression Model for Watch-Time Prediction in Short-video Recommendation0
Transferable Adversarial Robustness for Categorical Data via Universal Robust EmbeddingsCode0
CTRL: Connect Collaborative and Language Model for CTR Prediction0
Construction d'un système de recommandation basé sur des contraintes via des graphes de connaissances0
Gen-IR @ SIGIR 2023: The First Workshop on Generative Information Retrieval0
Personalized Federated Domain Adaptation for Item-to-Item Recommendation0
Large Language Model Augmented Narrative Driven RecommendationsCode0
STUDY: Socially Aware Temporally Causal Decoder Recommender Systems0
Hierarchical Reinforcement Learning for Modeling User Novelty-Seeking Intent in Recommender Systems0
A Survey on Explainability of Graph Neural Networks0
Système de recommandations basé sur les contraintes pour les simulations de gestion de crise0
Reducing Popularity Bias in Recommender Systems through AUC-Optimal Negative SamplingCode0
Semi-supervised Community Detection via Structural Similarity Metrics0
A Multi-Modal Latent-Features based Service Recommendation System for the Social Internet of Things0
Cook-Gen: Robust Generative Modeling of Cooking Actions from RecipesCode0
A Survey on Fairness-aware Recommender Systems0
Dynamic Neighborhood Construction for Structured Large Discrete Action SpacesCode0
Representer Point Selection for Explaining Regularized High-dimensional Models0
Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria RecommendationCode0
Robust Reinforcement Learning Objectives for Sequential Recommender SystemsCode0
The News Delivery Channel Recommendation Based on Granular Neural Network0
Human Body Shape Classification Based on a Single Image0
Graph Exploration Matters: Improving both individual-level and system-level diversity in WeChat Feed Recommender0
Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N RecommendationCode0
DotHash: Estimating Set Similarity Metrics for Link Prediction and Document DeduplicationCode0
Choosing the Right Weights: Balancing Value, Strategy, and Noise in Recommender Systems0
CARAMEL: A Succinct Read-Only Lookup Table via Compressed Static Functions0
Justification vs. Transparency: Why and How Visual Explanations in a Scientific Literature Recommender System0
Mitigating Exploitation Bias in Learning to Rank with an Uncertainty-aware Empirical Bayes Approach0
FARA: Future-aware Ranking Algorithm for Fairness OptimizationCode0
Efficient Document Embeddings via Self-Contrastive Bregman Divergence Learning0
Show:102550
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1KTUP (soft)HR@100.89Unverified
2Factorization with dictionary learningRMSE0.87Unverified
3Factorized EAERMSE0.86Unverified
4U-CFNRMSE0.86Unverified
5IGMCRMSE0.86Unverified
6FedGNNRMSE0.85Unverified
7NNMFRMSE0.84Unverified
8BSTRMSE0.84Unverified
9FedPerGNNRMSE0.84Unverified
10GHRSRMSE0.84Unverified
#ModelMetricClaimedVerifiedStatus
1LT-OCFRecall@200.19Unverified
2SSCFnDCG@200.06Unverified
3SANSAnDCG@200.06Unverified
4RLAE-DANnDCG@200.06Unverified
5HSTU+MoLHR@100.06Unverified
6BSPM-LMnDCG@200.06Unverified
7BSPM-EMnDCG@200.06Unverified
8Turbo-CFnDCG@200.06Unverified
9Emb-GCNnDCG@200.06Unverified
10NESCLnDCG@200.05Unverified
#ModelMetricClaimedVerifiedStatus
1GMCRMSE (u1 Splits)1Unverified
2GRALSRMSE (u1 Splits)0.95Unverified
3sRGCNNRMSE (u1 Splits)0.93Unverified
4WMLFFRMSE (u1 Splits)0.93Unverified
5FedGNNRMSE0.92Unverified
6Factorized EAERMSE (u1 Splits)0.92Unverified
7GRAEM / KPMFRMSE (u1 Splits)0.92Unverified
8Self-Supervised Exchangeable ModelRMSE (u1 Splits)0.91Unverified
9FedPerGNNRMSE0.91Unverified
10GC-MCRMSE (u1 Splits)0.91Unverified
#ModelMetricClaimedVerifiedStatus
1HyperMLnDCG@100.64Unverified
2LRMLnDCG@100.62Unverified
3CMLnDCG@100.53Unverified
4Multi-Gradient DescentRecall@200.42Unverified
5RecVAERecall@200.41Unverified
6VASPRecall@200.41Unverified
7H+Vamp GatedRecall@200.41Unverified
8RaCTRecall@200.4Unverified
9Mult-VAE PRRecall@200.4Unverified
10EASERecall@200.39Unverified
#ModelMetricClaimedVerifiedStatus
1U-RBMRMSE0.82Unverified
2FedGNNRMSE0.8Unverified
3Factorization with dictionary learningRMSE0.8Unverified
4U-CFNRMSE0.8Unverified
5FedPerGNNRMSE0.79Unverified
6I-AutoRecRMSE0.78Unverified
7GC-MCRMSE0.78Unverified
8I-CFNRMSE0.78Unverified
9SGD MFRMSE0.77Unverified
10CF-NADERMSE0.77Unverified
#ModelMetricClaimedVerifiedStatus
1ConvNCFnDCG@200.6Unverified
2NESCLnDCG@200.16Unverified
3RLAE-DANnDCG@200.16Unverified
4BSPM-EMnDCG@200.16Unverified
5MGDCFnDCG@200.16Unverified
6Emb-GCNnDCG@200.16Unverified
7LT-OCFnDCG@200.16Unverified
8BSPM-LMnDCG@200.16Unverified
9SimpleXnDCG@200.16Unverified
10LightGCNnDCG@200.16Unverified
#ModelMetricClaimedVerifiedStatus
1NESCLNDCG@200.06Unverified
2BSPM-EMNDCG@200.06Unverified
3RLAE-DANNDCG@200.06Unverified
4BSPM-LMNDCG@200.06Unverified
5MGDCFNDCG@200.06Unverified
6SimpleXNDCG@200.06Unverified
7Turbo-CFNDCG@200.06Unverified
8LT-OCFNDCG@200.05Unverified
9SSCFNDCG@200.05Unverified
10LightGCNNDCG@200.05Unverified
#ModelMetricClaimedVerifiedStatus
1H+Vamp GatednDCG@1000.41Unverified
2RecVAEnDCG@1000.39Unverified
3EASEnDCG@1000.39Unverified
4RaCTnDCG@1000.39Unverified
5Mult-VAE PRnDCG@1000.39Unverified
6Mult-DAEnDCG@1000.38Unverified
7∞-AEnDCG@1000.37Unverified
8LRMLnDCG@100.36Unverified
9CMLnDCG@100.29Unverified
10RATE-CSERecall@100.2Unverified
#ModelMetricClaimedVerifiedStatus
1GRALSRMSE0.83Unverified
2sRGCNNRMSE0.8Unverified
3Factorized EAERMSE0.74Unverified
4GC-MCRMSE0.73Unverified
5GRAEM / KPMFRMSE0.73Unverified
6MG-GATRMSE0.73Unverified
7IGMCRMSE0.72Unverified
8GLocal-KRMSE0.72Unverified
#ModelMetricClaimedVerifiedStatus
1UCCRRecall@100.22Unverified
2KERLRecall@10.06Unverified
3C2CRSRecall@10.05Unverified
4UniCRSRecall@10.05Unverified
5CRFRRecall@10.04Unverified
6CR-WalkerRecall@10.04Unverified
7KGSFRecall@10.04Unverified
8KBRDRecall@10.03Unverified
#ModelMetricClaimedVerifiedStatus
1CARCA Abs + ConHit@100.68Unverified
2ProxyRCAHit@100.63Unverified
3CARCA-RotatoryHit@100.62Unverified
4CARCAHit@100.58Unverified
5SSE-PTHit@100.5Unverified
6SASRecHit@100.49Unverified
7HetroFairMAP@200.14Unverified
#ModelMetricClaimedVerifiedStatus
1∞-AEAUC0.95Unverified
2FedGNNRMSE0.79Unverified
3FedPerGNNRMSE0.78Unverified
4GRALSRMSE0.71Unverified
5U-CFNRMSE0.7Unverified
6I-CFNRMSE0.69Unverified
7DGRecNDCG0.2Unverified
#ModelMetricClaimedVerifiedStatus
1GRALSRMSE1.24Unverified
2sRGCNNRMSE0.93Unverified
3GC-MCRMSE0.92Unverified
4Factorized EAERMSE0.91Unverified
5GRAEMRMSE0.89Unverified
6MG-GATRMSE0.88Unverified
7IGMCRMSE0.87Unverified
#ModelMetricClaimedVerifiedStatus
1EASEnDCG@1000.39Unverified
2SANSAnDCG@1000.39Unverified
3RecVAEnDCG@1000.33Unverified
4RaCTnDCG@1000.32Unverified
5Mult-VAE PRnDCG@1000.32Unverified
6Mult-DAEnDCG@1000.31Unverified
7CMLRecall@500.25Unverified
#ModelMetricClaimedVerifiedStatus
1TLSANAUC0.95Unverified
2ProxyRCAHit@100.81Unverified
3CARCA-Rotatory + Con.Hit@100.81Unverified
4CARCAHit@100.78Unverified
5SSE-PTHit@100.78Unverified
6SASRecHit@100.74Unverified
#ModelMetricClaimedVerifiedStatus
1GRALSRMSE38.04Unverified
2sRGCNNRMSE22.41Unverified
3GC-MCRMSE20.5Unverified
4Factorized EAERMSE20Unverified
5IGMCRMSE19.1Unverified
6MG-GATRMSE18.9Unverified
#ModelMetricClaimedVerifiedStatus
1SAERSAUC0.82Unverified
2RMHA-4Hit@100.77Unverified
3ProxyRCAHitRatio@ 10 (100 Neg. Samples)0.66Unverified
4CARCAHitRatio@ 10 (100 Neg. Samples)0.59Unverified
#ModelMetricClaimedVerifiedStatus
1GraphRecMAE0.82Unverified
2NSCR (Wang et al., 2017)MAE0.8Unverified
3DANSERMAE0.78Unverified
4HetroFairMAP@200.04Unverified