ThePlantGame: Actively Training Human Annotators for Domain-specific Crowdsourcing

Maximilien Servajean 1 Alexis Joly 1 Dennis Shasha 2 Julien Champ 1 Esther Pacitti 1
1 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : In a typical citizen science/crowdsourcing environment, the contributors label items. When there are few labels, it is straightforward to train contributors and judge the quality of their labels by giving a few examples with known answers. Neither is true when there are thousands of domain-specic labels and annotators with heterogeneous skills. This demo paper presents an Active User Training framework implemented as a serious game called The- PlantGame. It is based on a set of data-driven algorithms allowing to (i) actively train annotators, and (ii) evaluate the quality of contributors’ answers on new test items to optimize predictions.
Type de document :
Communication dans un congrès
ACM Multimedia 2016, Oct 2016, Amsterdam, Netherlands
Liste complète des métadonnées

Littérature citée [6 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01373769
Contributeur : Alexis Joly <>
Soumis le : lundi 3 octobre 2016 - 12:06:26
Dernière modification le : vendredi 20 juillet 2018 - 22:44:01
Document(s) archivé(s) le : vendredi 3 février 2017 - 13:51:49

Fichier

TPG-demo-ACMM.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01373769, version 1

Collections

Citation

Maximilien Servajean, Alexis Joly, Dennis Shasha, Julien Champ, Esther Pacitti. ThePlantGame: Actively Training Human Annotators for Domain-specific Crowdsourcing. ACM Multimedia 2016, Oct 2016, Amsterdam, Netherlands. 〈hal-01373769〉

Partager

Métriques

Consultations de la notice

816

Téléchargements de fichiers

85