When Less is Enough: Optimizations for Low-Cost Recommendation Systems
Social media platforms rely heavily on ad revenue, making cost-efficient recommendation systems essential for sustaining profitability while preserving user satisfaction, especially in regions with low Average Revenue Per User (ARPU).
Authors
- Danish Kalim (ORCID: https://orcid.org/0009-0004-0944-262X)
- Deepanshu Hardaha
- Shivansh Joshi
Institutions
- Hong Bang International University (VN)
Publication Details
- Published
- 2025-07-13
- DOI
- https://doi.org/10.1145/3726302.3730267
- Primary Topic
- Recommender Systems and Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00