A Kernel Hybridization NGram-Okapi for Indexing and Classification of Arabic Documents
Year: 2014
Journal of Information and Computing Science, Vol. 9 (2014), Iss. 2 : pp. 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.
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2024-JICS-22591
Journal of Information and Computing Science, Vol. 9 (2014), Iss. 2 : pp. 141–153
Published online: 2014-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 13