Designing Actionable and Interpretable Analytics Indicators for Improving Feedback in AI-Based Systems

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Published
2025-01-01
DOI
https://doi.org/10.5220/0013294300003932
Citations
1
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
2.48
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Designing Actionable and Interpretable Analytics Indicators for Improving Feedback in AI-Based Systems

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Explainable Artificial Intelligence (XAI)
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Designing Actionable and Interpretable Analytics Indicators for Improving Feedback in AI-Based Systems

Julien Broisin, Isabel Hilliger, Rafael Ferreira Mello, Esteban Villalobos, Ilmara Monteverde Martins Ramos, Esther Félix, Elaine Oliveira, Mar Pérez‐Sanagustín
article en
1 citations

Abstract

No abstract available for this paper.
Centre National de la Recherche Scientifique (FR), Université Toulouse III - Paul Sabatier (FR), Pontificia Universidad Católica de Chile (CL), Université Fédérale de Toulouse Midi-Pyrénées (FR), Université Toulouse-I-Capitole (FR), Institut de Recherche en Informatique de Toulouse (FR), Centro de Estudos e Sistemas Avançados do Recife (BR), Université Toulouse - Jean Jaurès (FR), Institut Polytechnique de Bordeaux (FR), Universidade Federal do Amazonas (BR)
Openalex Percentile: Top 11%
Explainable Artificial Intelligence (XAI)
2.48
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