Joint embedding-classifier learning for interpretable collaborative filtering.
Journal:
BMC bioinformatics
Published Date:
Jan 22, 2025
Abstract
BACKGROUND: Interpretability is a topical question in recommender systems, especially in healthcare applications. An interpretable classifier quantifies the importance of each input feature for the predicted item-user association in a non-ambiguous fashion.