تقرير
Harm Mitigation in Recommender Systems under User Preference Dynamics
| العنوان: | Harm Mitigation in Recommender Systems under User Preference Dynamics |
|---|---|
| المؤلفون: | Chee, Jerry, Kalyanaraman, Shankar, Ernala, Sindhu Kiranmai, Weinsberg, Udi, Dean, Sarah, Ioannidis, Stratis |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Information Retrieval, Computer Science - Computers and Society, Computer Science - Machine Learning |
| الوصف: | We consider a recommender system that takes into account the interplay between recommendations, the evolution of user interests, and harmful content. We model the impact of recommendations on user behavior, particularly the tendency to consume harmful content. We seek recommendation policies that establish a tradeoff between maximizing click-through rate (CTR) and mitigating harm. We establish conditions under which the user profile dynamics have a stationary point, and propose algorithms for finding an optimal recommendation policy at stationarity. We experiment on a semi-synthetic movie recommendation setting initialized with real data and observe that our policies outperform baselines at simultaneously maximizing CTR and mitigating harm. Comment: Recommender Systems; Harm Mitigation; Amplification; User Preference Modeling |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2406.09882 |
| رقم الأكسشن: | edsarx.2406.09882 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |