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 3651–3700 of 6047 papers

Title	Date	Tasks	Status
User recommendation system based on MIND dataset	Sep 6, 2022	Collaborative FilteringNews Recommendation	—Unverified
UserReg: A Simple but Strong Model for Rating Prediction	Feb 15, 2021	Collaborative FilteringPrediction	—Unverified
User Simulation for Evaluating Information Access Systems	Jun 14, 2023	Recommendation SystemsUser Simulation	—Unverified
User-specific Adaptive Fine-tuning for Cross-domain Recommendations	Jun 15, 2021	Recommendation SystemsTransfer Learning	—Unverified
User-Specific Bicluster-based Collaborative Filtering: Handling Preference Locality, Sparsity and Subjectivity	Nov 15, 2022	Collaborative FilteringDiversity	—Unverified
User Strategization and Trustworthy Algorithms	Dec 29, 2023	counterfactualRecommendation Systems	—Unverified
UserSumBench: A Benchmark Framework for Evaluating User Summarization Approaches	Aug 30, 2024	HallucinationRecommendation Systems	—Unverified
User Tampering in Reinforcement Learning Recommender Systems	Sep 9, 2021	Q-LearningRecommendation Systems	—Unverified
User Welfare Optimization in Recommender Systems with Competing Content Creators	Apr 28, 2024	Recommendation Systems	—Unverified
Using a Language Model in a Kiosk Recommender System at Fast-Food Restaurants	Feb 8, 2022	Language ModelingLanguage Modelling	—Unverified
Using a Personal Health Library-Enabled mHealth Recommender System for Self-Management of Diabetes Among Underserved Populations: Use Case for Knowledge Graphs and Linked Data	Mar 16, 2021	Knowledge GraphsManagement	—Unverified
Using Artificial Intelligence to Identify State Secrets	Nov 1, 2016	Recommendation Systems	—Unverified
Using coevolution and substitution of the fittest for health and well-being recommender systems	Nov 1, 2022	Recommendation Systems	—Unverified
Using Collaborative Filtering to Model Argument Selection	Sep 1, 2021	Collaborative Filteringmodel	—Unverified
Using consumer behavior data to reduce energy consumption in smart homes	Oct 1, 2015	Recommendation SystemsSequential Pattern Mining	—Unverified
Using consumer feedback from location-based services in PoI recommender systems for people with autism	Apr 21, 2022	Recommendation SystemsRetrieval	—Unverified
Using Image Fairness Representations in Diversity-Based Re-ranking for Recommendations	Sep 10, 2018	DiversityFairness	—Unverified
Using Interventions to Improve Out-of-Distribution Generalization of Text-Matching Recommendation Systems	Oct 7, 2022	Language ModellingOut-of-Distribution Generalization	—Unverified
Using Large-scale Heterogeneous Graph Representation Learning for Code Review Recommendations at Microsoft	Feb 4, 2022	Graph Representation LearningManagement	—Unverified
Using Learnable Physics for Real-Time Exercise Form Recommendations	Oct 11, 2023	FormRecommendation Systems	—Unverified
Using Machine Learning and Pattern-Based Methods for Identifying Elements in Chinese Judgment Documents of Civil Cases	Nov 1, 2022	Recommendation Systems	—Unverified
Using Mise-En-Scène Visual Features based on MPEG-7 and Deep Learning for Movie Recommendation	Apr 20, 2017	4kMovie Recommendation	—Unverified
Using Person Embedding to Enrich Features and Data Augmentation for Classification	Jun 30, 2022	BIG-bench Machine LearningClassification	—Unverified
Using Shortlists to Support Decision Making and Improve Recommender System Performance	Oct 26, 2015	Decision MakingMovie Recommendation	—Unverified
Using Social Media Background to Improve Cold-start Recommendation Deep Models	Jun 4, 2021	Recommendation Systems	—Unverified
Using the Context of User Feedback in Recommender Systems	Dec 15, 2016	Recommendation Systems	—Unverified
Using the Open Meta Kaggle Dataset to Evaluate Tripartite Recommendations in Data Markets	Aug 12, 2019	Collaborative FilteringRecommendation Systems	—Unverified
Using Topic Models in Content-Based News Recommender Systems	May 1, 2013	Recommendation SystemsTopic Models	—Unverified
Using user's local context to support local news	May 24, 2022	ArticlesRecommendation Systems	—Unverified
Using Wikipedia Editor Information to Build High-performance Recommender Systems	Jun 14, 2023	ArticlesRecommendation Systems	—Unverified
USM: Unbiased Survey Modeling for Limiting Negative User Experiences in Recommendation Systems	Dec 14, 2024	Recommendation Systems	—Unverified
Utility in Fashion with implicit feedback	Jun 30, 2018	MarketingRecommendation Systems	—Unverified
Utilizing Collaborative Filtering in a Personalized Research-Paper Recommendation System	Sep 28, 2024	Collaborative FilteringRecommendation Systems	—Unverified
Utilizing Imbalanced Data and Classification Cost Matrix to Predict Movie Preferences	Dec 4, 2018	ClassificationGeneral Classification	—Unverified
Utilizing Language Models for Tour Itinerary Recommendation	Nov 21, 2023	Recommendation Systems	—Unverified
Utilizing Speech Emotion Recognition and Recommender Systems for Negative Emotion Handling in Therapy Chatbots	Nov 18, 2023	ChatbotEmotion Recognition	—Unverified
Utilizing Textual Reviews in Latent Factor Models for Recommender Systems	Nov 16, 2021	Recommendation Systems	—Unverified
Validation of a recommender system for prompting omitted foods in online dietary assessment surveys	Mar 20, 2019	Recommendation Systems	—Unverified
Value-aware Recommendation based on Reinforced Profit Maximization in E-commerce Systems	Feb 3, 2019	Recommendation Systemsreinforcement-learning	—Unverified
Value Function Decomposition in Markov Recommendation Process	Jan 29, 2025	Recommendation Systems	—Unverified
Value Identification in Multistakeholder Recommender Systems for Humanities and Historical Research: The Case of the Digital Archive Monasterium.net	Sep 26, 2024	Recommendation Systems	—Unverified
Long-Term Value of Exploration: Measurements, Findings and Algorithms	May 12, 2023	Recommendation Systems	—Unverified
Value Penalized Q-Learning for Recommender Systems	Oct 15, 2021	Offline RLQ-Learning	—Unverified
Vamsa: Automated Provenance Tracking in Data Science Scripts	Jan 7, 2020	FairnessRecommendation Systems	—Unverified
Variance-Optimal Augmentation Logging for Counterfactual Evaluation in Contextual Bandits	Feb 3, 2022	counterfactualMulti-Armed Bandits	—Unverified
Exploration-Exploitation Motivated Variational Auto-Encoder for Recommender Systems	Jun 5, 2020	Collaborative FilteringRecommendation Systems	—Unverified
Variational Autoencoders for Highly Multivariate Spatial Point Processes Intensities	May 1, 2020	Collaborative FilteringPoint Processes	—Unverified
Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion	Sep 6, 2018	Bayesian InferenceRecommendation Systems	—Unverified
Variational Collaborative Learning for User Probabilistic Representation	Sep 22, 2018	Collaborative FilteringRecommendation Systems	—Unverified
Variation Autoencoder Based Network Representation Learning for Classification	Jul 1, 2017	ClassificationDocument Classification	—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