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cs.IR2023
Drifter: Efficient Online Feature Monitoring for Improved Data Integrity in Large-Scale Recommendation Systems
Blaž Škrlj, Nir Ki-Tov, Lee Edelist +5
Real-world production systems often grapple with maintaining data quality in large-scale, dynamic streams. We introduce Drifter, an efficient and lightweight system for online feat…
cs.IR2023
Unleash the Power of Context: Enhancing Large-Scale Recommender Systems with Context-Based Prediction Models
Jan Hartman, Assaf Klein, Davorin Kopič +1
In this work, we introduce the notion of Context-Based Prediction Models. A Context-Based Prediction Model determines the probability of a user's action (such as a click or a conve…