Answering N-Relation Natural Language Questions in the Commercial Domain

Elena Cabrio 1, 2 Catherine Faron-Zucker 1, 2 Fabien Gandon 1, 2 Amine Hallili 1, 2 Andrea G. B. Tettamanzi 1, 2
1 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
2 I3S - Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis
Abstract : This paper presents SynchroBot, a Natural Language Question Answering system in the Commercial Domain. It relies on an RDF dataset and an RDFS ontology that we have developed for the commercial domain of the mobile phone industry. We propose an approach to understand and interpret natural language questions, based on the use of regular expressions to identify both the properties connecting entities, and their values. These regex are automatically learned from a subset of our dataset with a genetic algorithm.
Type de document :
Communication dans un congrès
The IEEE/WIC/ACM International Conference on Web Intelligence, Dec 2015, Singapore, Singapore
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01187413
Contributeur : Catherine Faron Zucker <>
Soumis le : mercredi 27 juillet 2016 - 17:52:41
Dernière modification le : vendredi 29 juillet 2016 - 01:04:42

Fichier

synchrobot-WI-short.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01187413, version 1

Collections

UNICE | WIMMICS | INRIA | I3S

Citation

Elena Cabrio, Catherine Faron-Zucker, Fabien Gandon, Amine Hallili, Andrea G. B. Tettamanzi. Answering N-Relation Natural Language Questions in the Commercial Domain. The IEEE/WIC/ACM International Conference on Web Intelligence, Dec 2015, Singapore, Singapore. <hal-01187413>

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de
la notice

252

Téléchargements du document

56

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD