Copertina

Position Paper: Why the Shooting in the Dark Method Dominates Recommender Systems Practice; A Call to Abandon Anti-Utopian Thinking

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Rohde, David
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Information Retrieval Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Confounding is a Pervasive Problem in Real World Recommender Systems
di: Merkov, Alexander, et al.
Pubblicazione: (2025)

Anchored Alignment: Preventing Positional Collapse in Multimodal Recommender Systems
di: Jeong, Yonghun, et al.
Pubblicazione: (2026)

Probabilistic Rank and Reward: A Scalable Model for Slate Recommendation
di: Aouali, Imad, et al.
Pubblicazione: (2022)

INTERPOS: Interaction Rhythm Guided Positional Morphing for Mobile App Recommender Systems
di: Maqbool, M. H., et al.
Pubblicazione: (2025)

Causal Feature Selection Method for Contextual Multi-Armed Bandits in Recommender System
di: Zhao, Zhenyu, et al.
Pubblicazione: (2024)

Temporal Graph Neural Network-Powered Paper Recommendation on Dynamic Citation Networks
di: Shen, Junhao, et al.
Pubblicazione: (2024)

MIARec: Mutual-influence-aware Heterogeneous Network Embedding for Scientific Paper Recommendation
di: Xie, Wenjin, et al.
Pubblicazione: (2025)

PolyRecommender: A Multimodal Recommendation System for Polymer Discovery
di: Wang, Xin, et al.
Pubblicazione: (2025)

SPGL: Enhancing Session-based Recommendation with Single Positive Graph Learning
di: Liang, Tiantian, et al.
Pubblicazione: (2024)

Continual Recommender Systems
di: Yoo, Hyunsik, et al.
Pubblicazione: (2025)

Dataset-Agnostic Recommender Systems
di: Wijaya, Tri Kurniawan, et al.
Pubblicazione: (2025)

System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processes
di: Agarwal, Arpit, et al.
Pubblicazione: (2024)

One Pass, Any Order: Position-Invariant Listwise Reranking for LLM-Based Recommendation
di: Bito, Ethan, et al.
Pubblicazione: (2026)

Understanding Fairness in Recommender Systems: A Healthcare Perspective
di: Kecki, Veronica, et al.
Pubblicazione: (2024)

ProReco: A Process Discovery Recommender System
di: Huang, Tsung-Hao, et al.
Pubblicazione: (2025)

Co-clustering for Federated Recommender System
di: He, Xinrui, et al.
Pubblicazione: (2024)

The Potential of AutoML for Recommender Systems
di: Vente, Tobias, et al.
Pubblicazione: (2024)

Neural Click Models for Recommender Systems
di: Shirokikh, Mikhail, et al.
Pubblicazione: (2024)

Evaluation on Entity Matching in Recommender Systems
di: Huang, Zihan, et al.
Pubblicazione: (2026)

The Unreasonable Effectiveness of Data for Recommender Systems
di: Abdou, Youssef
Pubblicazione: (2026)

Tweedie Regression for Video Recommendation System
di: Zheng, Yan, et al.
Pubblicazione: (2025)

Generalized Embedding Machines for Recommender Systems
di: Yang, Enneng, et al.
Pubblicazione: (2020)

From AutoRecSys to AutoRecLab: A Call to Build, Evaluate, and Govern Autonomous Recommender-Systems Research Labs
di: Beel, Joeran, et al.
Pubblicazione: (2025)

DIIT: A Domain-Invariant Information Transfer Method for Industrial Cross-Domain Recommendation
di: Huang, Heyuan, et al.
Pubblicazione: (2024)

Measuring Recency Bias In Sequential Recommendation Systems
di: Oh, Jeonglyul, et al.
Pubblicazione: (2024)

Modeling Attrition in Recommender Systems with Departing Bandits
di: Ben-Porat, Omer, et al.
Pubblicazione: (2022)

Understanding Distribution Structure on Calibrated Recommendation Systems
di: da Silva, Diego Correa, et al.
Pubblicazione: (2025)

The Environmental Impact of Ensemble Techniques in Recommender Systems
di: Nitschke, Jannik
Pubblicazione: (2025)

Towards Practical Large-scale Dynamical Heterogeneous Graph Embedding: Cold-start Resilient Recommendation
di: Long, Mabiao, et al.
Pubblicazione: (2025)

A Thorough Performance Benchmarking on Lightweight Embedding-based Recommender Systems
di: Tran, Hung Vinh, et al.
Pubblicazione: (2024)

A Unified Causal Framework for Auditing Recommender Systems for Ethical Concerns
di: Sharma, Vibhhu, et al.
Pubblicazione: (2024)

Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing
di: Liu, Wenyi, et al.
Pubblicazione: (2024)

ContextGNN: Beyond Two-Tower Recommendation Systems
di: Yuan, Yiwen, et al.
Pubblicazione: (2024)

e-Fold Cross-Validation for Recommender-System Evaluation
di: Baumgart, Moritz, et al.
Pubblicazione: (2024)

Beyond Item Dissimilarities: Diversifying by Intent in Recommender Systems
di: Wang, Yuyan, et al.
Pubblicazione: (2024)

TD3: Tucker Decomposition Based Dataset Distillation Method for Sequential Recommendation
di: Zhang, Jiaqing, et al.
Pubblicazione: (2025)

Incentive-Aware Recommender Systems in Two-Sided Markets
di: Dai, Xiaowu, et al.
Pubblicazione: (2022)

Towards Principled Learning for Re-ranking in Recommender Systems
di: Li, Qunwei, et al.
Pubblicazione: (2025)

Does Weighting Improve Matrix Factorization for Recommender Systems?
di: Ayoub, Alex, et al.
Pubblicazione: (2025)

Creator-Side Recommender System: Challenges, Designs, and Applications
di: Chen, Xiaoshuang, et al.
Pubblicazione: (2025)