Contributions to the use of analogical proportions for machine learning : theoretical properties and application to recommendation. (Contributions à l'usage des proportions analogiques pour l'apprentissage artificiel : propriétés théoriques et application à la recommandation).
N. Hug. Paul Sabatier University, Toulouse, France, (2017)
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%0 Thesis
%1 phd/hal/Hug17
%A Hug, Nicolas
%D 2017
%K
%T Contributions to the use of analogical proportions for machine learning : theoretical properties and application to recommendation. (Contributions à l'usage des proportions analogiques pour l'apprentissage artificiel : propriétés théoriques et application à la recommandation).
@phdthesis{phd/hal/Hug17,
added-at = {2023-12-14T15:19:23.000+0100},
author = {Hug, Nicolas},
biburl = {https://www.bibsonomy.org/bibtex/2488dfe436a599237a0905ab5c86c7335/admin},
ee = {https://tel.archives-ouvertes.fr/tel-01887642},
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school = {Paul Sabatier University, Toulouse, France},
timestamp = {2023-12-14T15:19:23.000+0100},
title = {Contributions to the use of analogical proportions for machine learning : theoretical properties and application to recommendation. (Contributions à l'usage des proportions analogiques pour l'apprentissage artificiel : propriétés théoriques et application à la recommandation).},
year = 2017
}