Measuring the Predictability of Recommender Systems using Structural Complexity Metrics
Fuente:
arXiv
Guardado en:
| Autores principales: | Abeliuk, Andrés, Valderrama, Alfonso, Campos, Simón, Mendoza, Marcelo |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Measuring Recency Bias In Sequential Recommendation Systems
por: Oh, Jeonglyul, et al.
Publicado: (2024)
por: Oh, Jeonglyul, et al.
Publicado: (2024)
Understanding Distribution Structure on Calibrated Recommendation Systems
por: da Silva, Diego Correa, et al.
Publicado: (2025)
por: da Silva, Diego Correa, et al.
Publicado: (2025)
Improved Diversity-Promoting Collaborative Metric Learning for Recommendation
por: Bao, Shilong, et al.
Publicado: (2024)
por: Bao, Shilong, et al.
Publicado: (2024)
A Metric for MLLM Alignment in Large-scale Recommendation
por: Zhang, Yubin, et al.
Publicado: (2025)
por: Zhang, Yubin, et al.
Publicado: (2025)
Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation
por: Shi, Wentao, et al.
Publicado: (2024)
por: Shi, Wentao, et al.
Publicado: (2024)
Identifying Offline Metrics that Predict Online Impact: A Pragmatic Strategy for Real-World Recommender Systems
por: Wilm, Timo, et al.
Publicado: (2025)
por: Wilm, Timo, et al.
Publicado: (2025)
Metric Learning for Tag Recommendation: Tackling Data Sparsity and Cold Start Issues
por: Luo, Yuanshuai, et al.
Publicado: (2024)
por: Luo, Yuanshuai, et al.
Publicado: (2024)
The Bandit's Blind Spot: The Critical Role of User State Representation in Recommender Systems
por: Pires, Pedro R., et al.
Publicado: (2026)
por: Pires, Pedro R., et al.
Publicado: (2026)
On (Normalised) Discounted Cumulative Gain as an Off-Policy Evaluation Metric for Top-$n$ Recommendation
por: Jeunen, Olivier, et al.
Publicado: (2023)
por: Jeunen, Olivier, et al.
Publicado: (2023)
Continual Recommender Systems
por: Yoo, Hyunsik, et al.
Publicado: (2025)
por: Yoo, Hyunsik, et al.
Publicado: (2025)
Value-Aware Product Recommendation by Customer Segmentation using a suitable High-Dimensional Similarity Measure
por: Acosta, María Florencia, et al.
Publicado: (2026)
por: Acosta, María Florencia, et al.
Publicado: (2026)
LiveGraph: Active-Structure Neural Re-ranking for Exercise Recommendation
por: Fu, Rong, et al.
Publicado: (2026)
por: Fu, Rong, et al.
Publicado: (2026)
Calibrating the Predictions for Top-N Recommendations
por: Sato, Masahiro
Publicado: (2024)
por: Sato, Masahiro
Publicado: (2024)
RPAF: A Reinforcement Prediction-Allocation Framework for Cache Allocation in Large-Scale Recommender Systems
por: Su, Shuo, et al.
Publicado: (2024)
por: Su, Shuo, et al.
Publicado: (2024)
Interpretive Efficiency: Information-Geometric Foundations of Data Usefulness
por: Katende, Ronald
Publicado: (2025)
por: Katende, Ronald
Publicado: (2025)
PolyRecommender: A Multimodal Recommendation System for Polymer Discovery
por: Wang, Xin, et al.
Publicado: (2025)
por: Wang, Xin, et al.
Publicado: (2025)
Dataset-Agnostic Recommender Systems
por: Wijaya, Tri Kurniawan, et al.
Publicado: (2025)
por: Wijaya, Tri Kurniawan, et al.
Publicado: (2025)
System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processes
por: Agarwal, Arpit, et al.
Publicado: (2024)
por: Agarwal, Arpit, et al.
Publicado: (2024)
Turbo-CF: Matrix Decomposition-Free Graph Filtering for Fast Recommendation
por: Park, Jin-Duk, et al.
Publicado: (2024)
por: Park, Jin-Duk, et al.
Publicado: (2024)
EasyRL4Rec: An Easy-to-use Library for Reinforcement Learning Based Recommender Systems
por: Yu, Yuanqing, et al.
Publicado: (2024)
por: Yu, Yuanqing, et al.
Publicado: (2024)
Co-clustering for Federated Recommender System
por: He, Xinrui, et al.
Publicado: (2024)
por: He, Xinrui, et al.
Publicado: (2024)
The Potential of AutoML for Recommender Systems
por: Vente, Tobias, et al.
Publicado: (2024)
por: Vente, Tobias, et al.
Publicado: (2024)
Neural Click Models for Recommender Systems
por: Shirokikh, Mikhail, et al.
Publicado: (2024)
por: Shirokikh, Mikhail, et al.
Publicado: (2024)
Evaluation on Entity Matching in Recommender Systems
por: Huang, Zihan, et al.
Publicado: (2026)
por: Huang, Zihan, et al.
Publicado: (2026)
The Unreasonable Effectiveness of Data for Recommender Systems
por: Abdou, Youssef
Publicado: (2026)
por: Abdou, Youssef
Publicado: (2026)
Tweedie Regression for Video Recommendation System
por: Zheng, Yan, et al.
Publicado: (2025)
por: Zheng, Yan, et al.
Publicado: (2025)
Generalized Embedding Machines for Recommender Systems
por: Yang, Enneng, et al.
Publicado: (2020)
por: Yang, Enneng, et al.
Publicado: (2020)
Incentivizing High-Quality Content in Online Recommender Systems
por: Hu, Xinyan, et al.
Publicado: (2023)
por: Hu, Xinyan, et al.
Publicado: (2023)
Training-free Adjustable Polynomial Graph Filtering for Ultra-fast Multimodal Recommendation
por: Roh, Yu-Seung, et al.
Publicado: (2025)
por: Roh, Yu-Seung, et al.
Publicado: (2025)
Criteria-Aware Graph Filtering: Extremely Fast Yet Accurate Multi-Criteria Recommendation
por: Park, Jin-Duk, et al.
Publicado: (2025)
por: Park, Jin-Duk, et al.
Publicado: (2025)
Modeling Attrition in Recommender Systems with Departing Bandits
por: Ben-Porat, Omer, et al.
Publicado: (2022)
por: Ben-Porat, Omer, et al.
Publicado: (2022)
The Environmental Impact of Ensemble Techniques in Recommender Systems
por: Nitschke, Jannik
Publicado: (2025)
por: Nitschke, Jannik
Publicado: (2025)
Leveraging Member-Group Relations via Multi-View Graph Filtering for Effective Group Recommendation
por: Kim, Chae-Hyun, et al.
Publicado: (2025)
por: Kim, Chae-Hyun, et al.
Publicado: (2025)
ID Embedding as Subtle Features of Content and Structure for Multimodal Recommendation
por: Liu, Yuting, et al.
Publicado: (2023)
por: Liu, Yuting, et al.
Publicado: (2023)
Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution
por: Xu, Cong, et al.
Publicado: (2023)
por: Xu, Cong, et al.
Publicado: (2023)
Scaling Down, Serving Fast: Compressing and Deploying Efficient LLMs for Recommendation Systems
por: Behdin, Kayhan, et al.
Publicado: (2025)
por: Behdin, Kayhan, et al.
Publicado: (2025)
Generative Regression Based Watch Time Prediction for Short-Video Recommendation
por: Ma, Hongxu, et al.
Publicado: (2024)
por: Ma, Hongxu, et al.
Publicado: (2024)
Relative Advantage Debiasing for Watch-Time Prediction in Short-Video Recommendation
por: Liu, Emily, et al.
Publicado: (2025)
por: Liu, Emily, et al.
Publicado: (2025)
Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing
por: Liu, Wenyi, et al.
Publicado: (2024)
por: Liu, Wenyi, et al.
Publicado: (2024)
ContextGNN: Beyond Two-Tower Recommendation Systems
por: Yuan, Yiwen, et al.
Publicado: (2024)
por: Yuan, Yiwen, et al.
Publicado: (2024)
Ejemplares similares
-
Measuring Recency Bias In Sequential Recommendation Systems
por: Oh, Jeonglyul, et al.
Publicado: (2024) -
Understanding Distribution Structure on Calibrated Recommendation Systems
por: da Silva, Diego Correa, et al.
Publicado: (2025) -
Improved Diversity-Promoting Collaborative Metric Learning for Recommendation
por: Bao, Shilong, et al.
Publicado: (2024) -
A Metric for MLLM Alignment in Large-scale Recommendation
por: Zhang, Yubin, et al.
Publicado: (2025) -
Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation
por: Shi, Wentao, et al.
Publicado: (2024)