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 la 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 XML

Authors: Ait Ali Yahia Yassine ; Amrouche Karima

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]


Share

Consultation statistics

This page has been seen 116 times.
This article's PDF has been downloaded 121 times.