MT-Based Transparent Arabization of the Internet TARJIM.COM

Chalabi, Achraf

doi:10.1007/3-540-39965-8_19

Cited by 3 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, indexing Arabic language documents remains a big challenge towards its integration in the information technology, given its power and its wealth. Automatic indexing of Arabic documents raises major problems [4,5]:…”

Section: Introductionmentioning

confidence: 99%

An Accuracy-Enhanced Stemming Algorithm for Arabic Information Retrieval

Bessou¹,

Touahria²

2014

NNW

View full text Add to dashboard Cite

This paper provides a method for indexing and retrieving Arabic texts, based on natural language processing. Our approach exploits the notion of template in word stemming and replaces the words by their stems. This technique has proven to be effective, since it has returned significant relevant retrieval results by decreasing silence during the retrieval phase. Series of experiments have been conducted to test the performance of the proposed algorithm ESAIR (Enhanced Stemmer for Arabic Information Retrieval). The results obtained indicate that the algorithm extracts the exact root with an accuracy rate up to 96% and hence, improving information retrieval.

show abstract

Section: Introductionmentioning

confidence: 99%

An Accuracy-Enhanced Stemming Algorithm for Arabic Information Retrieval

Bessou¹,

Touahria²

2014

NNW

View full text Add to dashboard Cite

show abstract

An Exploration Into The Various Types Of Ambiguity In Arabic Language: A Pedagogical Study

Harbi¹

2016

TheIJSSHI

View full text Add to dashboard Cite

Arabic Documents Classification by a Radial Basis Hybridization

Zaki

Mammass

Ennaji

et al. 2021

International Journal of Mathematical Models and Methods in Applied Sciences

View full text Add to dashboard Cite

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.

show abstract

MT-Based Transparent Arabization of the Internet TARJIM.COM

Cited by 3 publications

References 0 publications

An Accuracy-Enhanced Stemming Algorithm for Arabic Information Retrieval

An Accuracy-Enhanced Stemming Algorithm for Arabic Information Retrieval

An Exploration Into The Various Types Of Ambiguity In Arabic Language: A Pedagogical Study

Arabic Documents Classification by a Radial Basis Hybridization

Contact Info

Product

Resources

About