@Article{JICS-9-141,
author = {Taher Zaki , Driss Mammass , Abdellatif Ennaji and Stéphane Nicolas},
title = {A Kernel Hybridization NGram-Okapi for Indexing and Classification of Arabic Documents},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {9},
number = {2},
pages = {141--153},
abstract = { In  this  paper,  we  propose  a  hybrid  system  for  contextual  and  semantic  indexing  of  Arabic 
documents, bringing an improvement to classical models based on n-grams and the Okapi model. This new 
approach  takes  into  account  the  concept  of  the  semantic  vicinity  of  terms.  We  proceed  in  fact  by  the 
calculation  of  similarity  between  words  using  an  hybridization  of      NGRAMs-OKAPI  statistical  measures 
and a kernel function in order to identify relevant descriptors. Terminological resources such as graphs and 
semantic dictionaries are integrated into the system to improve the indexing and the classification processes. 
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22591.html}
}