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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 2901–2950 of 6047 papers

Title	Date	Tasks	Status
Cross-domain recommender system using Generalized Canonical Correlation Analysis	Sep 15, 2019	Collaborative FilteringRecommendation Systems	—Unverified
Facets of Fairness in Search and Recommendation	Jul 16, 2020	DiversityFairness	—Unverified
Improved theoretical guarantee for rank aggregation via spectral method	Sep 7, 2023	Recommendation Systems	—Unverified
Cross-domain User Preference Learning for Cold-start Recommendation	Dec 7, 2021	Recommendation Systems	—Unverified
Attention-based Dynamic Subspace Learners for Medical Image Analysis	Jun 18, 2022	ClusteringImage Clustering	—Unverified
Improvements on Recommender System based on Mathematical Principles	Apr 26, 2023	Recommendation Systems	—Unverified
Improving Accountability in Recommender Systems Research Through Reproducibility	Jan 31, 2021	Information RetrievalRecommendation Systems	—Unverified
Improving Accuracy and Diversity in Matching of Recommendation with Diversified Preference Network	Feb 7, 2021	DiversityGraph Attention	—Unverified
Cross-Modal Alignment with Mixture Experts Neural Network for Intral-City Retail Recommendation	Sep 17, 2020	cross-modal alignmentImage to text	—Unverified
Improving Collaborative Filtering Recommendation via Graph Learning	Nov 6, 2023	Collaborative FilteringGraph Learning	—Unverified
A Correlation Maximization Approach for Cross Domain Co-Embeddings	Sep 10, 2018	Recommendation Systems	—Unverified
Improving Content Recommendation: Knowledge Graph-Based Semantic Contrastive Learning for Diversity and Cold-Start Users	Mar 27, 2024	Contrastive LearningDescriptive	—Unverified
Eye Tracking as a Source of Implicit Feedback in Recommender Systems: A Preliminary Analysis	May 12, 2023	Collaborative FilteringMovie Recommendation	—Unverified
Extreme Multilabel Classification for Specialist Doctor Recommendation with Implicit Feedback and Limited Patient Metadata	Aug 21, 2023	Recommendation Systems	—Unverified
Improving Conversational Recommendation Systems’ Quality with Context-Aware Item Meta-Information	Jan 16, 2022	Conversational RecommendationKnowledge Graphs	—Unverified
Improving Conversational Recommendation Systems’ Quality with Context-Aware Item Meta-Information	Jul 1, 2022	Conversational RecommendationKnowledge Graphs	—Unverified
A General Offline Reinforcement Learning Framework for Interactive Recommendation	Oct 1, 2023	Interactive RecommendationRecommendation Systems	—Unverified
Binary Classification with XOR Queries: Fundamental Limits and An Efficient Algorithm	Jan 31, 2020	Active LearningAttribute	—Unverified
Improving Conversational Recommender System via Contextual and Time-Aware Modeling with Less Domain-Specific Knowledge	Sep 23, 2022	Recommendation Systems	—Unverified
A Comprehensive Survey on Retrieval Methods in Recommender Systems	Jul 11, 2024	BenchmarkingRecommendation Systems	—Unverified
Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation	Nov 11, 2022	Decision MakingRecommendation Systems	—Unverified
Intent Disentanglement and Feature Self-supervision for Novel Recommendation	Jun 28, 2021	DisentanglementRecommendation Systems	—Unverified
Improving feature interactions at Pinterest under industry constraints	Dec 2, 2024	GPURecommendation Systems	—Unverified
CRUISE on Quantum Computing for Feature Selection in Recommender Systems	Jul 3, 2024	counterfactualfeature selection	—Unverified
Extreme Learning to Rank via Low Rank Assumption	Jul 1, 2018	Learning-To-RankRecommendation Systems	—Unverified
Improving incremental recommenders with online bagging	Mar 26, 2018	Recommendation Systems	—Unverified
Extremal GloVe: Theoretically Accurate Distributed Word Embedding by Tail Inference	Apr 27, 2022	Recommendation SystemsWord Embeddings	—Unverified
ClusterSeq: Enhancing Sequential Recommender Systems with Clustering based Meta-Learning	Jul 25, 2023	ClusteringMeta-Learning	—Unverified
Improving Items and Contexts Understanding with Descriptive Graph for Conversational Recommendation	Apr 11, 2023	BenchmarkingConversational Recommendation	—Unverified
Improving LLM Interpretability and Performance via Guided Embedding Refinement for Sequential Recommendation	Apr 15, 2025	Recommendation SystemsSequential Recommendation	—Unverified
Clustering on Multiple Incomplete Datasets via Collective Kernel Learning	Oct 4, 2013	ClusteringRecommendation Systems	—Unverified
Improving Long-Term Metrics in Recommendation Systems using Short-Horizon Reinforcement Learning	Jun 1, 2021	Offline RLRecommendation Systems	—Unverified
Improving Matrix Completion by Exploiting Rating Ordinality in Graph Neural Networks	Mar 7, 2024	Graph Neural NetworkMatrix Completion	—Unverified
Improving Multi-Interest Network with Stable Learning	Jul 14, 2022	Recommendation Systems	—Unverified
Efficiently Tackling Million-Dimensional Multiobjective Problems: A Direction Sampling and Fine-Tuning Approach	Apr 8, 2023	Multiobjective OptimizationRecommendation Systems	—Unverified
Improving Next-Application Prediction with Deep Personalized-Attention Neural Network	Nov 9, 2021	Recommendation Systems	—Unverified
Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques	May 14, 2014	News RecommendationRecommendation Systems	—Unverified
Improving Out-of-Vocabulary Handling in Recommendation Systems	Mar 27, 2024	Recommendation Systems	—Unverified
Improving Personalized Explanation Generation through Visualization	May 1, 2022	DiversityExplainable Recommendation	—Unverified
CUPCF: Combining Users Preferences in Collaborative Filtering for Better Recommendation	Aug 13, 2019	Collaborative FilteringRecommendation Systems	—Unverified
Improving Rating and Relevance with Point-of-Interest Recommender System	Feb 17, 2022	Recommendation SystemsRetrieval	—Unverified
CUPID: A Real-Time Session-Based Reciprocal Recommendation System for a One-on-One Social Discovery Platform	Oct 8, 2024	Recommendation Systems	—Unverified
A General Neural Causal Model for Interactive Recommendation	Oct 30, 2023	counterfactualCounterfactual Inference	—Unverified
Extracting Implicit Social Relation for Social Recommendation Techniques in User Rating Prediction	Dec 5, 2016	Recommendation SystemsRelation	—Unverified
Extending MovieLens-32M to Provide New Evaluation Objectives	Apr 2, 2025	Information RetrievalRecommendation Systems	—Unverified
Improving Recommendation Fairness without Sensitive Attributes Using Multi-Persona LLMs	May 26, 2025	FairnessRecommendation Systems	—Unverified
Improving Recommendation Relevance by simulating User Interest	Feb 3, 2023	Recommendation SystemsSensitivity	—Unverified
Improving Recommendation System Serendipity Through Lexicase Selection	May 18, 2023	DiversityRecommendation Systems	—Unverified
Improving Recommendation Systems with User Personality Inferred from Product Reviews	Mar 9, 2023	Decision MakingMusic Recommendation	—Unverified
Clustering is Efficient for Approximate Maximum Inner Product Search	Jul 21, 2015	ClusteringRecommendation Systems	—Unverified

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All datasets MovieLens 1M Amazon-Book MovieLens 100K MovieLens 20M MovieLens 10M Gowalla Yelp2018 Netflix Douban Monti ReDial Amazon Beauty Douban

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	KTUP (soft)	HR@10	0.89	—	Unverified
2	Factorization with dictionary learning	RMSE	0.87	—	Unverified
3	Factorized EAE	RMSE	0.86	—	Unverified
4	U-CFN	RMSE	0.86	—	Unverified
5	IGMC	RMSE	0.86	—	Unverified
6	FedGNN	RMSE	0.85	—	Unverified
7	NNMF	RMSE	0.84	—	Unverified
8	BST	RMSE	0.84	—	Unverified
9	FedPerGNN	RMSE	0.84	—	Unverified
10	GHRS	RMSE	0.84	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LT-OCF	Recall@20	0.19	—	Unverified
2	SSCF	nDCG@20	0.06	—	Unverified
3	SANSA	nDCG@20	0.06	—	Unverified
4	RLAE-DAN	nDCG@20	0.06	—	Unverified
5	HSTU+MoL	HR@10	0.06	—	Unverified
6	BSPM-LM	nDCG@20	0.06	—	Unverified
7	BSPM-EM	nDCG@20	0.06	—	Unverified
8	Turbo-CF	nDCG@20	0.06	—	Unverified
9	Emb-GCN	nDCG@20	0.06	—	Unverified
10	NESCL	nDCG@20	0.05	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GMC	RMSE (u1 Splits)	1	—	Unverified
2	GRALS	RMSE (u1 Splits)	0.95	—	Unverified
3	sRGCNN	RMSE (u1 Splits)	0.93	—	Unverified
4	WMLFF	RMSE (u1 Splits)	0.93	—	Unverified
5	FedGNN	RMSE	0.92	—	Unverified
6	Factorized EAE	RMSE (u1 Splits)	0.92	—	Unverified
7	GRAEM / KPMF	RMSE (u1 Splits)	0.92	—	Unverified
8	Self-Supervised Exchangeable Model	RMSE (u1 Splits)	0.91	—	Unverified
9	FedPerGNN	RMSE	0.91	—	Unverified
10	GC-MC	RMSE (u1 Splits)	0.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HyperML	nDCG@10	0.64	—	Unverified
2	LRML	nDCG@10	0.62	—	Unverified
3	CML	nDCG@10	0.53	—	Unverified
4	Multi-Gradient Descent	Recall@20	0.42	—	Unverified
5	RecVAE	Recall@20	0.41	—	Unverified
6	VASP	Recall@20	0.41	—	Unverified
7	H+Vamp Gated	Recall@20	0.41	—	Unverified
8	RaCT	Recall@20	0.4	—	Unverified
9	Mult-VAE PR	Recall@20	0.4	—	Unverified
10	EASE	Recall@20	0.39	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	U-RBM	RMSE	0.82	—	Unverified
2	FedGNN	RMSE	0.8	—	Unverified
3	Factorization with dictionary learning	RMSE	0.8	—	Unverified
4	U-CFN	RMSE	0.8	—	Unverified
5	FedPerGNN	RMSE	0.79	—	Unverified
6	I-AutoRec	RMSE	0.78	—	Unverified
7	GC-MC	RMSE	0.78	—	Unverified
8	I-CFN	RMSE	0.78	—	Unverified
9	SGD MF	RMSE	0.77	—	Unverified
10	CF-NADE	RMSE	0.77	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ConvNCF	nDCG@20	0.6	—	Unverified
2	NESCL	nDCG@20	0.16	—	Unverified
3	RLAE-DAN	nDCG@20	0.16	—	Unverified
4	BSPM-EM	nDCG@20	0.16	—	Unverified
5	MGDCF	nDCG@20	0.16	—	Unverified
6	Emb-GCN	nDCG@20	0.16	—	Unverified
7	LT-OCF	nDCG@20	0.16	—	Unverified
8	BSPM-LM	nDCG@20	0.16	—	Unverified
9	SimpleX	nDCG@20	0.16	—	Unverified
10	LightGCN	nDCG@20	0.16	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	NESCL	NDCG@20	0.06	—	Unverified
2	BSPM-EM	NDCG@20	0.06	—	Unverified
3	RLAE-DAN	NDCG@20	0.06	—	Unverified
4	BSPM-LM	NDCG@20	0.06	—	Unverified
5	MGDCF	NDCG@20	0.06	—	Unverified
6	SimpleX	NDCG@20	0.06	—	Unverified
7	Turbo-CF	NDCG@20	0.06	—	Unverified
8	LT-OCF	NDCG@20	0.05	—	Unverified
9	SSCF	NDCG@20	0.05	—	Unverified
10	LightGCN	NDCG@20	0.05	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	H+Vamp Gated	nDCG@100	0.41	—	Unverified
2	RecVAE	nDCG@100	0.39	—	Unverified
3	EASE	nDCG@100	0.39	—	Unverified
4	RaCT	nDCG@100	0.39	—	Unverified
5	Mult-VAE PR	nDCG@100	0.39	—	Unverified
6	Mult-DAE	nDCG@100	0.38	—	Unverified
7	∞-AE	nDCG@100	0.37	—	Unverified
8	LRML	nDCG@10	0.36	—	Unverified
9	CML	nDCG@10	0.29	—	Unverified
10	RATE-CSE	Recall@10	0.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GRALS	RMSE	0.83	—	Unverified
2	sRGCNN	RMSE	0.8	—	Unverified
3	Factorized EAE	RMSE	0.74	—	Unverified
4	GC-MC	RMSE	0.73	—	Unverified
5	GRAEM / KPMF	RMSE	0.73	—	Unverified
6	MG-GAT	RMSE	0.73	—	Unverified
7	IGMC	RMSE	0.72	—	Unverified
8	GLocal-K	RMSE	0.72	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UCCR	Recall@10	0.22	—	Unverified
2	KERL	Recall@1	0.06	—	Unverified
3	C2CRS	Recall@1	0.05	—	Unverified
4	UniCRS	Recall@1	0.05	—	Unverified
5	CRFR	Recall@1	0.04	—	Unverified
6	CR-Walker	Recall@1	0.04	—	Unverified
7	KGSF	Recall@1	0.04	—	Unverified
8	KBRD	Recall@1	0.03	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CARCA Abs + Con	Hit@10	0.68	—	Unverified
2	ProxyRCA	Hit@10	0.63	—	Unverified
3	CARCA-Rotatory	Hit@10	0.62	—	Unverified
4	CARCA	Hit@10	0.58	—	Unverified
5	SSE-PT	Hit@10	0.5	—	Unverified
6	SASRec	Hit@10	0.49	—	Unverified
7	HetroFair	MAP@20	0.14	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	∞-AE	AUC	0.95	—	Unverified
2	FedGNN	RMSE	0.79	—	Unverified
3	FedPerGNN	RMSE	0.78	—	Unverified
4	GRALS	RMSE	0.71	—	Unverified
5	U-CFN	RMSE	0.7	—	Unverified
6	I-CFN	RMSE	0.69	—	Unverified
7	DGRec	NDCG	0.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GRALS	RMSE	1.24	—	Unverified
2	sRGCNN	RMSE	0.93	—	Unverified
3	GC-MC	RMSE	0.92	—	Unverified
4	Factorized EAE	RMSE	0.91	—	Unverified
5	GRAEM	RMSE	0.89	—	Unverified
6	MG-GAT	RMSE	0.88	—	Unverified
7	IGMC	RMSE	0.87	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	EASE	nDCG@100	0.39	—	Unverified
2	SANSA	nDCG@100	0.39	—	Unverified
3	RecVAE	nDCG@100	0.33	—	Unverified
4	RaCT	nDCG@100	0.32	—	Unverified
5	Mult-VAE PR	nDCG@100	0.32	—	Unverified
6	Mult-DAE	nDCG@100	0.31	—	Unverified
7	CML	Recall@50	0.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TLSAN	AUC	0.95	—	Unverified
2	ProxyRCA	Hit@10	0.81	—	Unverified
3	CARCA-Rotatory + Con.	Hit@10	0.81	—	Unverified
4	CARCA	Hit@10	0.78	—	Unverified
5	SSE-PT	Hit@10	0.78	—	Unverified
6	SASRec	Hit@10	0.74	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GRALS	RMSE	38.04	—	Unverified
2	sRGCNN	RMSE	22.41	—	Unverified
3	GC-MC	RMSE	20.5	—	Unverified
4	Factorized EAE	RMSE	20	—	Unverified
5	IGMC	RMSE	19.1	—	Unverified
6	MG-GAT	RMSE	18.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SAERS	AUC	0.82	—	Unverified
2	RMHA-4	Hit@10	0.77	—	Unverified
3	ProxyRCA	HitRatio@ 10 (100 Neg. Samples)	0.66	—	Unverified
4	CARCA	HitRatio@ 10 (100 Neg. Samples)	0.59	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GraphRec	MAE	0.82	—	Unverified
2	NSCR (Wang et al., 2017)	MAE	0.8	—	Unverified
3	DANSER	MAE	0.78	—	Unverified
4	HetroFair	MAP@20	0.04	—	Unverified