Ait Ali Yahia Yassine ; Amrouche Karima - Réseaux bayésiens jumelés et noyau de Fisher pondéré pour la classification de documents XML

arima:1971 - Revue Africaine de Recherche en Informatique et Mathématiques Appliquées, November 9, 2014, Volume 17 - 2014 - Special issue CARI'12 - https://doi.org/10.46298/arima.1971
Réseaux bayésiens jumelés et noyau de Fisher pondéré pour la classification de documents XMLArticle

Authors: Ait Ali Yahia Yassine 1; Amrouche Karima 1

  • 1 École Nationale Supérieure d'Informatique [Alger]

In this paper, we are presenting a learning model for XML document classification based on Bayesian networks. Then, we are proposing a model which simplifies the arborescent representation of the XML document that we have, named coupled model and we will see that this approach improves the response time and keeps the same performances of the classification. Then, we will study an extension of this generative model to the discriminating model thanks to the formalism of the Fisher’s kernel. At last, we have applied a ponderation of the structure components of the Fisher’s vector. We finish by presenting the obtained results on the XML collection by using the CBS and SVM methods


Volume: Volume 17 - 2014 - Special issue CARI'12
Published on: November 9, 2014
Submitted on: April 11, 2014
Keywords: XML documents, Bayesian networks, Fisher’s kernel, classification, discriminating models.,[INFO] Computer Science [cs],[MATH] Mathematics [math]

Consultation statistics

This page has been seen 278 times.
This article's PDF has been downloaded 314 times.