• Corpus ID: 221819409

Modeling Online Behavior in Recommender Systems: The Importance of Temporal Context

@article{Filipovic2021ModelingOB,
  title={Modeling Online Behavior in Recommender Systems: The Importance of Temporal Context},
  author={Milena Filipovic and Blagoj Mitrevski and Diego Antognini and Emma Lejal Glaude and Boi Faltings and Claudiu Cristian Musat},
  journal={ArXiv},
  year={2021},
  volume={abs/2009.08978}
}
Simulating online recommender system performance is notoriously difficult and the discrepancy between the online and offline behaviors is typically not accounted for in offline evaluations. Recommender systems research tends to evaluate model performance on randomly sampled targets, yet the same systems are later used to predict user behavior sequentially from a fixed point in time. This disparity permits weaknesses to go unnoticed until the model is deployed in a production setting. We first… 

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