Publishing Partner: Cambridge University Press CUP Extra Publisher Login

New from Cambridge University Press!

ad

Revitalizing Endangered Languages

Edited by Justyna Olko & Julia Sallabank

Revitalizing Endangered Languages "This guidebook provides ideas and strategies, as well as some background, to help with the effective revitalization of endangered languages. It covers a broad scope of themes including effective planning, benefits, wellbeing, economic aspects, attitudes and ideologies."


We Have a New Site!

With the help of your donations we have been making good progress on designing and launching our new website! Check it out at https://linguistlist.org/!
***We are still in our beta stages for the new site--if you have any feedback, be sure to let us know at webdevlinguistlist.org***

Academic Paper


Title: POS-tagging arabic texts: A novel approach based on ant colony
Author: CHIRAZ OTHMANE
Author: FERIEL FRAJ
Author: ICHRAF LIMAM
Linguistic Field: Computational Linguistics; Text/Corpus Linguistics
Subject Language: Arabic, Standard
Abstract: The specificities of the Arabic language, mainly agglutination and vocalization make the task of POS-tagging more difficult than for Indo-European languages. Consequently, POS-tagging texts with good accuracy remains a challenging problem for Arabic language processing applications. In this work, we consider the task of POS-tagging as an optimization problem modeled as a graph whose nodes correspond to all possible grammatical tags given by a morphological analyzer for words in a sentence and the goal is to find the best path (sequence of tags) in this graph. To resolve this problem, we propose a novel approach based on ant colony. Ant colony-based algorithms are among the most efficient methods to resolve optimization problems modeled as a graph. The collaboration of ants having various knowledge creates a collective intelligence and increases efficiency. We have performed experiments on both vocalized and non-vocalized texts and tested two different tagsets containing fine and coarse grained composite tags. The obtained results showed good accuracy rates and hence, the benefits of swarm intelligence for the POS-tagging problem.

CUP AT LINGUIST

This article appears IN Natural Language Engineering Vol. 23, Issue 3, which you can READ on Cambridge's site .

Return to TOC.

View the full article for free in the current issue of
Cambridge Extra Magazine!
Add a new paper
Return to Academic Papers main page
Return to Directory of Linguists main page