Copertina

Intersectional Two-sided Fairness in Recommendation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Yifan, Sun, Peijie, Ma, Weizhi, Zhang, Min, Zhang, Yuan, Jiang, Peng, Ma, Shaoping
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Information Retrieval Computers and Society Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Ensuring User-side Fairness in Dynamic Recommender Systems
di: Yoo, Hyunsik, et al.
Pubblicazione: (2023)

A Tutorial On Intersectionality in Fair Rankings
di: Criscuolo, Chiara, et al.
Pubblicazione: (2025)

Consumer-side Fairness in Recommender Systems: A Systematic Survey of Methods and Evaluation
di: Vassøy, Bjørnar, et al.
Pubblicazione: (2023)

Fair Recommendations with Limited Sensitive Attributes: A Distributionally Robust Optimization Approach
di: Shi, Tianhao, et al.
Pubblicazione: (2024)

Social Choice for Heterogeneous Fairness in Recommendation
di: Aird, Amanda, et al.
Pubblicazione: (2024)

ReChorus2.0: A Modular and Task-Flexible Recommendation Library
di: Li, Jiayu, et al.
Pubblicazione: (2024)

Recommender for Its Purpose: Repeat and Exploration in Food Delivery Recommendations
di: Li, Jiayu, et al.
Pubblicazione: (2024)

Large Language Models as Evaluators for Recommendation Explanations
di: Zhang, Xiaoyu, et al.
Pubblicazione: (2024)

FACTER: Fairness-Aware Conformal Thresholding and Prompt Engineering for Enabling Fair LLM-Based Recommender Systems
di: Fayyazi, Arya, et al.
Pubblicazione: (2025)

Aiming at the Target: Filter Collaborative Information for Cross-Domain Recommendation
di: Li, Hanyu, et al.
Pubblicazione: (2024)

Are Recommenders Self-Aware? Label-Free Recommendation Performance Estimation via Model Uncertainty
di: Li, Jiayu, et al.
Pubblicazione: (2025)

Fairness in Ranking under Disparate Uncertainty
di: Rastogi, Richa, et al.
Pubblicazione: (2023)

Properties of Group Fairness Metrics for Rankings
di: Schumacher, Tobias, et al.
Pubblicazione: (2022)

When Fair Ranking Meets Uncertain Inference
di: Ghosh, Avijit, et al.
Pubblicazione: (2021)

A Situation-aware Enhancer for Personalized Recommendation
di: Li, Jiayu, et al.
Pubblicazione: (2024)

Interpolating Item and User Fairness in Multi-Sided Recommendations
di: Chen, Qinyi, et al.
Pubblicazione: (2023)

Synthetic CVs To Build and Test Fairness-Aware Hiring Tools
di: Saldivar, Jorge, et al.
Pubblicazione: (2025)

EasyRL4Rec: An Easy-to-use Library for Reinforcement Learning Based Recommender Systems
di: Yu, Yuanqing, et al.
Pubblicazione: (2024)

AdaS&S: a One-Shot Supernet Approach for Automatic Embedding Size Search in Deep Recommender System
di: Wei, He, et al.
Pubblicazione: (2024)

Harm Mitigation in Recommender Systems under User Preference Dynamics
di: Chee, Jerry, et al.
Pubblicazione: (2024)

Uncertainty and Fairness Awareness in LLM-Based Recommendation Systems
di: Sah, Chandan Kumar, et al.
Pubblicazione: (2026)

A Counterfactual Approach for Addressing Individual User Unfairness in Collaborative Recommender System
di: Baidya, Nikita, et al.
Pubblicazione: (2026)

Enhancing Collaborative Filtering-Based Course Recommendations by Exploiting Time-to-Event Information with Survival Analysis
di: Gharahighehi, Alireza, et al.
Pubblicazione: (2025)

Multi-view Attention Fusion of Heterogeneous Hypergraph with Dynamic Behavioral Profiling for Personalized Learning Resource Recommendation
di: Xie, Tao, et al.
Pubblicazione: (2026)

Collaborative-Enhanced Prediction of Spending on Newly Downloaded Mobile Games under Consumption Uncertainty
di: Sun, Peijie, et al.
Pubblicazione: (2024)

To Recommend or Not: Recommendability Identification in Conversations with Pre-trained Language Models
di: Wang, Zhefan, et al.
Pubblicazione: (2024)

PEOAT: Personalization-Guided Evolutionary Question Assembly for One-Shot Adaptive Testing
di: Yu, Xiaoshan, et al.
Pubblicazione: (2025)

Measuring Individual User Fairness with User Similarity and Effectiveness Disparity
di: Rampisela, Theresia Veronika, et al.
Pubblicazione: (2026)

Mixed Supervised Graph Contrastive Learning for Recommendation
di: Zhang, Weizhi, et al.
Pubblicazione: (2024)

Sequential Recommendation with Latent Relations based on Large Language Model
di: Yang, Shenghao, et al.
Pubblicazione: (2024)

Introducing EEG Analyses to Help Personal Music Preference Prediction
di: He, Zhiyu, et al.
Pubblicazione: (2024)

Common Sense Enhanced Knowledge-based Recommendation with Large Language Model
di: Yang, Shenghao, et al.
Pubblicazione: (2024)

User-Creator Feature Polarization in Recommender Systems with Dual Influence
di: Lin, Tao, et al.
Pubblicazione: (2024)

APAO: Adaptive Prefix-Aware Optimization for Generative Recommendation
di: Yu, Yuanqing, et al.
Pubblicazione: (2026)

Enhancing Learning Path Recommendation via Multi-task Learning
di: Nasrin, Afsana, et al.
Pubblicazione: (2025)

Deep Uncertainty-Based Explore for Index Construction and Retrieval in Recommendation System
di: Jiang, Xin, et al.
Pubblicazione: (2024)

Enhancing Math Learning in an LMS Using AI-Driven Question Recommendations
di: Råmunddal, Justus
Pubblicazione: (2025)

A Comprehensive Survey on Deep Learning Techniques in Educational Data Mining
di: Lin, Yuanguo, et al.
Pubblicazione: (2023)

Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation
di: Zhang, Weizhi, et al.
Pubblicazione: (2024)

Recommender Systems for Good (RS4Good): Survey of Use Cases and a Call to Action for Research that Matters
di: Jannach, Dietmar, et al.
Pubblicazione: (2024)