Harm Mitigation in Recommender Systems under User Preference Dynamics
Fuente:
arXiv
Guardado en:
| Autores principales: | Chee, Jerry, Kalyanaraman, Shankar, Ernala, Sindhu Kiranmai, Weinsberg, Udi, Dean, Sarah, Ioannidis, Stratis |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Ensuring User-side Fairness in Dynamic Recommender Systems
por: Yoo, Hyunsik, et al.
Publicado: (2023)
por: Yoo, Hyunsik, et al.
Publicado: (2023)
Datasets for Navigating Sensitive Topics in Recommendation Systems
por: Kovacs, Amelia, et al.
Publicado: (2025)
por: Kovacs, Amelia, et al.
Publicado: (2025)
A Counterfactual Approach for Addressing Individual User Unfairness in Collaborative Recommender System
por: Baidya, Nikita, et al.
Publicado: (2026)
por: Baidya, Nikita, et al.
Publicado: (2026)
Aligning Recommendations with User Popularity Preferences
por: Schirmer, Mona, et al.
Publicado: (2026)
por: Schirmer, Mona, et al.
Publicado: (2026)
Cross-Platform Digital Discourse Analysis of the Israel-Hamas Conflict: Sentiment, Topics, and Event Dynamics
por: Antonakaki, Despoina, et al.
Publicado: (2025)
por: Antonakaki, Despoina, et al.
Publicado: (2025)
Mirroring Users: Towards Building Preference-aligned User Simulator with User Feedback in Recommendation
por: Wei, Tianjun, et al.
Publicado: (2025)
por: Wei, Tianjun, et al.
Publicado: (2025)
Accounting for AI and Users Shaping One Another: The Role of Mathematical Models
por: Dean, Sarah, et al.
Publicado: (2024)
por: Dean, Sarah, et al.
Publicado: (2024)
Minimizing Live Experiments in Recommender Systems: User Simulation to Evaluate Preference Elicitation Policies
por: Hsu, Chih-Wei, et al.
Publicado: (2024)
por: Hsu, Chih-Wei, et al.
Publicado: (2024)
User-Creator Feature Polarization in Recommender Systems with Dual Influence
por: Lin, Tao, et al.
Publicado: (2024)
por: Lin, Tao, et al.
Publicado: (2024)
Measuring Strategization in Recommendation: Users Adapt Their Behavior to Shape Future Content
por: Cen, Sarah H., et al.
Publicado: (2024)
por: Cen, Sarah H., et al.
Publicado: (2024)
Modeling User Preferences as Distributions for Optimal Transport-Based Cross-Domain Recommendation under Non-Overlapping Settings
por: Xiao, Ziyin, et al.
Publicado: (2025)
por: Xiao, Ziyin, et al.
Publicado: (2025)
Multi-view Attention Fusion of Heterogeneous Hypergraph with Dynamic Behavioral Profiling for Personalized Learning Resource Recommendation
por: Xie, Tao, et al.
Publicado: (2026)
por: Xie, Tao, et al.
Publicado: (2026)
Intersectional Two-sided Fairness in Recommendation
por: Wang, Yifan, et al.
Publicado: (2024)
por: Wang, Yifan, et al.
Publicado: (2024)
Social Choice for Heterogeneous Fairness in Recommendation
por: Aird, Amanda, et al.
Publicado: (2024)
por: Aird, Amanda, et al.
Publicado: (2024)
Food Pairing Unveiled: Exploring Recipe Creation Dynamics through Recommender Systems
por: Palermo, Giovanni, et al.
Publicado: (2024)
por: Palermo, Giovanni, et al.
Publicado: (2024)
Interpolating Item and User Fairness in Multi-Sided Recommendations
por: Chen, Qinyi, et al.
Publicado: (2023)
por: Chen, Qinyi, et al.
Publicado: (2023)
Filter Bubble or Homogenization? Disentangling the Long-Term Effects of Recommendations on User Consumption Patterns
por: Anwar, Md Sanzeed, et al.
Publicado: (2024)
por: Anwar, Md Sanzeed, et al.
Publicado: (2024)
Oracle-guided Dynamic User Preference Modeling for Sequential Recommendation
por: Xia, Jiafeng, et al.
Publicado: (2024)
por: Xia, Jiafeng, et al.
Publicado: (2024)
Fair Recommendations with Limited Sensitive Attributes: A Distributionally Robust Optimization Approach
por: Shi, Tianhao, et al.
Publicado: (2024)
por: Shi, Tianhao, et al.
Publicado: (2024)
Enhancing Collaborative Filtering-Based Course Recommendations by Exploiting Time-to-Event Information with Survival Analysis
por: Gharahighehi, Alireza, et al.
Publicado: (2025)
por: Gharahighehi, Alireza, et al.
Publicado: (2025)
Leveraging User-Generated Reviews for Recommender Systems with Dynamic Headers
por: Vashishtha, Shanu, et al.
Publicado: (2024)
por: Vashishtha, Shanu, et al.
Publicado: (2024)
Consumer-side Fairness in Recommender Systems: A Systematic Survey of Methods and Evaluation
por: Vassøy, Bjørnar, et al.
Publicado: (2023)
por: Vassøy, Bjørnar, et al.
Publicado: (2023)
Dynamic User Interest Augmentation via Stream Clustering and Memory Networks in Large-Scale Recommender Systems
por: Liu, Peng, et al.
Publicado: (2024)
por: Liu, Peng, et al.
Publicado: (2024)
Fairness in Ranking under Disparate Uncertainty
por: Rastogi, Richa, et al.
Publicado: (2023)
por: Rastogi, Richa, et al.
Publicado: (2023)
Preference and Concurrence Aware Bayesian Graph Neural Networks for Recommender Systems
por: Gu, Hongjian, et al.
Publicado: (2023)
por: Gu, Hongjian, et al.
Publicado: (2023)
Designing and Evaluating an Educational Recommender System with Different Levels of User Control
por: Ain, Qurat Ul, et al.
Publicado: (2025)
por: Ain, Qurat Ul, et al.
Publicado: (2025)
Advancing Sustainability via Recommender Systems: A Survey
por: Zhou, Xin, et al.
Publicado: (2024)
por: Zhou, Xin, et al.
Publicado: (2024)
De-centering the (Traditional) User: Multistakeholder Evaluation of Recommender Systems
por: Burke, Robin, et al.
Publicado: (2025)
por: Burke, Robin, et al.
Publicado: (2025)
A Simulation Framework for Studying Systemic Effects of Feedback Loops in Recommender Systems
por: Barlacchi, Gabriele, et al.
Publicado: (2025)
por: Barlacchi, Gabriele, et al.
Publicado: (2025)
Measuring Individual User Fairness with User Similarity and Effectiveness Disparity
por: Rampisela, Theresia Veronika, et al.
Publicado: (2026)
por: Rampisela, Theresia Veronika, et al.
Publicado: (2026)
FACTER: Fairness-Aware Conformal Thresholding and Prompt Engineering for Enabling Fair LLM-Based Recommender Systems
por: Fayyazi, Arya, et al.
Publicado: (2025)
por: Fayyazi, Arya, et al.
Publicado: (2025)
AURO: Reinforcement Learning for Adaptive User Retention Optimization in Recommender Systems
por: Xue, Zhenghai, et al.
Publicado: (2023)
por: Xue, Zhenghai, et al.
Publicado: (2023)
Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning
por: Han, Xiao, et al.
Publicado: (2024)
por: Han, Xiao, et al.
Publicado: (2024)
Recommender Systems for Good (RS4Good): Survey of Use Cases and a Call to Action for Research that Matters
por: Jannach, Dietmar, et al.
Publicado: (2024)
por: Jannach, Dietmar, et al.
Publicado: (2024)
Modeling Churn in Recommender Systems with Aggregated Preferences
por: Keinan, Gur, et al.
Publicado: (2025)
por: Keinan, Gur, et al.
Publicado: (2025)
Analyzing and Mitigating Repetitions in Trip Recommendation
por: Shu, Wenzheng, et al.
Publicado: (2025)
por: Shu, Wenzheng, et al.
Publicado: (2025)
Breaker: Removing Shortcut Cues with User Clustering for Single-slot Recommendation System
por: Wang, Chao, et al.
Publicado: (2025)
por: Wang, Chao, et al.
Publicado: (2025)
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)
Shilling Recommender Systems by Generating Side-feature-aware Fake User Profiles
por: Wang, Yuanrong, et al.
Publicado: (2025)
por: Wang, Yuanrong, et al.
Publicado: (2025)
Balanced Co-Clustering of Users and Items for Embedding Table Compression in Recommender Systems
por: Jiang, Runhao, et al.
Publicado: (2026)
por: Jiang, Runhao, et al.
Publicado: (2026)
Ejemplares similares
-
Ensuring User-side Fairness in Dynamic Recommender Systems
por: Yoo, Hyunsik, et al.
Publicado: (2023) -
Datasets for Navigating Sensitive Topics in Recommendation Systems
por: Kovacs, Amelia, et al.
Publicado: (2025) -
A Counterfactual Approach for Addressing Individual User Unfairness in Collaborative Recommender System
por: Baidya, Nikita, et al.
Publicado: (2026) -
Aligning Recommendations with User Popularity Preferences
por: Schirmer, Mona, et al.
Publicado: (2026) -
Cross-Platform Digital Discourse Analysis of the Israel-Hamas Conflict: Sentiment, Topics, and Event Dynamics
por: Antonakaki, Despoina, et al.
Publicado: (2025)