h(odor): Interactive Discovery of Hypotheses on the Structure-Odor Relationship in Neuroscience

Abstract : From a molecule to the brain perception, olfaction is a complex phenomenon that remains to be fully understood in neuroscience. Latest studies reveal that the physico-chemical properties of volatile molecules can partly explain the odor perception. Neuroscientists are then looking for new hypotheses to guide their research: physico-chemical descriptors distinguishing a subset of perceived odors. To answer this problem, we present the platform h(odor) that implements descriptive rule discovery algorithms suited for this task. Most importantly, the ol-faction experts can interact with the discovery algorithm to guide the search in a huge description space w.r.t their non-formalized background knowledge thanks to an ergonomic user interface.
Type de document :
Communication dans un congrès
ECML/PKDD 2016 (Demo), Sep 2016, Riva del Garda, Italy. ECML/PKDD 2016 (Demo), 2016, ECML/PKDD 2016 (Demo)
Liste complète des métadonnées

Littérature citée [7 références]  Voir  Masquer  Télécharger

https://hal.archives-ouvertes.fr/hal-01346679
Contributeur : Guillaume Bosc <>
Soumis le : mardi 19 juillet 2016 - 14:24:20
Dernière modification le : jeudi 8 février 2018 - 11:10:31

Fichier

pkdd16.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01346679, version 1

Citation

Guillaume Bosc, Marc Plantevit, Jean-François Boulicaut, Moustafa Bensafi, Mehdi Kaytoue. h(odor): Interactive Discovery of Hypotheses on the Structure-Odor Relationship in Neuroscience. ECML/PKDD 2016 (Demo), Sep 2016, Riva del Garda, Italy. ECML/PKDD 2016 (Demo), 2016, ECML/PKDD 2016 (Demo). 〈hal-01346679〉

Partager

Métriques

Consultations de la notice

155

Téléchargements de fichiers

143