Year: 2023
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Authors: Singh, Mayank, Ray, Emily, Ferradou, Marc, Barraza-Urbina, Andrea
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4385474589