Interpretable taxonomy extraction from digital assets metadata using automated unsupervised decision tree learning

DOI10.1134/s199508022301002xOpenAlexW4377003248WikidataQ122954059 ScholiaQ122954059MaRDI QIDQ6040336

I. Baimuratov

Publication date: 25 May 2023

Published in: Lobachevskii Journal of Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1134/s199508022301002x

zbMATH Keywords

unsupervised learningdecision treetaxonomy extractionhyperparameter optimizationknowledge graphdigital asset managementinterpretable clustering

Mathematics Subject Classification ID

Computer science (68-XX) Game theory, economics, finance, and other social and behavioral sciences (91-XX)

Cites Work

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• Interpretable clustering using unsupervised binary trees
• Silhouettes: a graphical aid to the interpretation and validation of cluster analysis

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