Metric@CustomerN: Evaluating Metrics at a Customer Level in E-Commerce

07/31/2023

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by   Mayank Singh, et al.

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Accuracy measures such as Recall, Precision, and Hit Rate have been a standard way of evaluating Recommendation Systems. The assumption is to use a fixed Top-N to represent them. We propose that median impressions viewed from historical sessions per diner be used as a personalized value for N. We present preliminary exploratory results and list future steps to improve upon and evaluate the efficacy of these personalized metrics.