XML document classification effectively using improved high-performance factor

2022 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Latha Parthiban ◽  
S. Sahunthala ◽  
Angelina Geetha
Keyword(s):  
High Performance ◽  
Document Classification ◽  
Performance Factor ◽  
Xml Document

XML document classification based on ELM

2011 ◽  
Vol 74 (16) ◽  
pp. 2444-2451 ◽  
Author(s):  
Xiang-guo Zhao ◽  
Guoren Wang ◽  
Xin Bi ◽  
Peizhen Gong ◽  
Yuhai Zhao
Keyword(s):  
Document Classification ◽  
Xml Document

scholarly journals Réseaux bayésiens jumelés et noyau de Fisher pondéré pour la classification de documents XML

2014 ◽  
Vol Volume 17 - 2014 - Special... ◽  
Author(s):  
Ait Ali Yahia Yassine ◽  
Amrouche Karima
Keyword(s):  
Response Time ◽  
Bayesian Networks ◽  
Coupled Model ◽  
Learning Model ◽  
Document Classification ◽  
Generative Model ◽  
Xml Document ◽  
International Audience

International audience 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

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