Transparency and precision in the age of AI: evaluation of explainability-enhanced recommendation systems

In today’s information age, recommender systems have become an essential tool to filter and personalize the massive data flow to users. However, these systems’ increasing complexity and opaque nature have raised concerns about transparency and user trust. Lack of explainability in recommendations ca...

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Bibliographic Details

Published in:	Frontiers in Artificial Intelligence
Main Authors:	Jaime Govea, Rommel Gutierrez, William Villegas-Ch
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2024-09-01
Subjects:	recommendation systems explainability in AI transparency and trust in AI machine learning artificial intelligence
Online Access:	https://www.frontiersin.org/articles/10.3389/frai.2024.1410790/full