Image de couverture de livre

A Comprehensive Survey of Evaluation Techniques for Recommendation Systems

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Jadon, Aryan, Patil, Avinash
Format:	Preprint
Publié:	2023
Sujets:	Information Retrieval Artificial Intelligence Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Graph Foundation Models for Recommendation: A Comprehensive Survey
par: Wu, Bin, et autres
Publié: (2025)

Semantic Search and Recommendation Algorithm
par: Duhan, Aryan, et autres
Publié: (2024)

A Survey on Popularity Bias in Recommender Systems
par: Klimashevskaia, Anastasiia, et autres
Publié: (2023)

A Survey of Latent Factor Models in Recommender Systems
par: Alshbanat, Hind I., et autres
Publié: (2024)

Enhancing Domain-Specific Retrieval-Augmented Generation: Synthetic Data Generation and Evaluation using Reasoning Models
par: Jadon, Aryan, et autres
Publié: (2025)

Consumer-side Fairness in Recommender Systems: A Systematic Survey of Methods and Evaluation
par: Vassøy, Bjørnar, et autres
Publié: (2023)

A Comprehensive Survey on Deep Graph Representation Learning
par: Ju, Wei, et autres
Publié: (2023)

Impression-Aware Recommender Systems
par: Maurera, Fernando B. Pérez, et autres
Publié: (2023)

Machine Unlearning for Recommendation Systems: An Insight
par: Sachdeva, Bhavika, et autres
Publié: (2024)

From AutoRecSys to AutoRecLab: A Call to Build, Evaluate, and Govern Autonomous Recommender-Systems Research Labs
par: Beel, Joeran, et autres
Publié: (2025)

Review of Explainable Graph-Based Recommender Systems
par: Markchom, Thanet, et autres
Publié: (2024)

Modeling Churn in Recommender Systems with Aggregated Preferences
par: Keinan, Gur, et autres
Publié: (2025)

Does It Look Sequential? An Analysis of Datasets for Evaluation of Sequential Recommendations
par: Klenitskiy, Anton, et autres
Publié: (2024)

Evaluating Podcast Recommendations with Profile-Aware LLM-as-a-Judge
par: Fabbri, Francesco, et autres
Publié: (2025)

Large Language Models as Recommender Systems: A Study of Popularity Bias
par: Lichtenberg, Jan Malte, et autres
Publié: (2024)

Ripple Knowledge Graph Convolutional Networks For Recommendation Systems
par: Li, Chen, et autres
Publié: (2023)

Robust Reinforcement Learning Objectives for Sequential Recommender Systems
par: Mozifian, Melissa, et autres
Publié: (2023)

Extracting Interaction-Aware Monosemantic Concepts in Recommender Systems
par: Arviv, Dor, et autres
Publié: (2025)

Talos: Optimizing Top-$K$ Accuracy in Recommender Systems
par: Zhang, Shengjia, et autres
Publié: (2026)

Navigating the Future of Federated Recommendation Systems with Foundation Models
par: Li, Zhiwei, et autres
Publié: (2024)

Exploring Feature-based Knowledge Distillation for Recommender System: A Frequency Perspective
par: Zhu, Zhangchi, et autres
Publié: (2024)

BPL: Bias-adaptive Preference Distillation Learning for Recommender System
par: Kang, SeongKu, et autres
Publié: (2025)

Weightless Neural Networks for Continuously Trainable Personalized Recommendation Systems
par: Latif, Rafayel, et autres
Publié: (2025)

CADMR: Cross-Attention and Disentangled Learning for Multimodal Recommender Systems
par: Khalafaoui, Yasser, et autres
Publié: (2024)

A Parameter Update Balancing Algorithm for Multi-task Ranking Models in Recommendation Systems
par: Yuan, Jun, et autres
Publié: (2024)

Mem-Rec: Memory Efficient Recommendation System using Alternative Representation
par: Jha, Gopi Krishna, et autres
Publié: (2023)

Pareto Front Approximation for Multi-Objective Session-Based Recommender Systems
par: Wilm, Timo, et autres
Publié: (2024)

What Data is Really Necessary? A Feasibility Study of Inference Data Minimization for Recommender Systems
par: Leysen, Jens, et autres
Publié: (2025)

Not All Candidates are Created Equal: A Heterogeneity-Aware Approach to Pre-ranking in Recommender Systems
par: Tong, Pengfei, et autres
Publié: (2026)

Deep Learning Model Acceleration and Optimization Strategies for Real-Time Recommendation Systems
par: Shao, Junli, et autres
Publié: (2025)

Enhancing Performance and Scalability of Large-Scale Recommendation Systems with Jagged Flash Attention
par: Xu, Rengan, et autres
Publié: (2024)

Epistemic Uncertainty-aware Recommendation Systems via Bayesian Deep Ensemble Learning
par: Cheraghi, Radin, et autres
Publié: (2025)

Break Out of a Pigeonhole: A Unified Framework for Examining Miscalibration, Bias, and Stereotype in Recommender Systems
par: Ahn, Yongsu, et autres
Publié: (2023)

RL-MPCA: A Reinforcement Learning Based Multi-Phase Computation Allocation Approach for Recommender Systems
par: Zhou, Jiahong, et autres
Publié: (2023)

A Knowledge Graph and Deep Learning-Based Semantic Recommendation Database System for Advertisement Retrieval and Personalization
par: Wang, Tangtang, et autres
Publié: (2025)

Advancing Loss Functions in Recommender Systems: A Comparative Study with a Rényi Divergence-Based Solution
par: Zhang, Shengjia, et autres
Publié: (2025)

Save, Revisit, Retain: A Scalable Framework for Enhancing User Retention in Large-Scale Recommender Systems
par: Jiang, Weijie, et autres
Publié: (2025)

Identifying Offline Metrics that Predict Online Impact: A Pragmatic Strategy for Real-World Recommender Systems
par: Wilm, Timo, et autres
Publié: (2025)

PSLF: A PID Controller-incorporated Second-order Latent Factor Analysis Model for Recommender System
par: Wang, Jialiang, et autres
Publié: (2024)

Rethinking ANN-based Retrieval: Multifaceted Learnable Index for Large-scale Recommendation System
par: Zhang, Jiang, et autres
Publié: (2026)