
		<paper>
			<loc>https://jjcit.org/paper/238</loc>
			<title>PROCESSING TOOLS FOR CORPUS LINGUISTICS: A CASE STUDY ON ARABIC HISTORICAL CORPUS</title>
			<doi>10.5455/jjcit.71-1714507767</doi>
			<authors>Bassam Hammo,Sane Yagi</authors>
			<keywords>Historical Arabic corpus,Corpus tools,Concordancer,Learning Arabic,Data normalization,Semantic shifting</keywords>
			<citation>3</citation>
			<views>3296</views>
			<downloads>671</downloads>
			<received_date>10-May-2024</received_date>
			<revised_date>  2-Jul.-2024</revised_date>
			<accepted_date>  29-Jul.-2024</accepted_date>
			<abstract>This  paper  explores  the  development,  design and reconstruction  of  a  Historical  Arabic  Corpus  (HAC),  which 
covers more than 1600 years of uninterrupted language use. The study emphasizes the technical aspects followed 
to enhance the system and provide a usable concordancer, along with simple experiments conducted on the corpus 
and the concordancer. Arabic has a rich literary and cultural heritage spanning thousands of years. The inclusion 
of  digital  resources  and  the  advancement  in  natural  language processing  (NLP)  technology  have  made  Arabic 
historical corpora increasingly crucial for researchers and learners worldwide. By integrating HAC and its tools 
into Arabic language learning, learners can delve deeper into vocabulary and culture and gain valuable insights 
that improve  their  language skills  and understanding of Arabic.  This  combination of human guidance and NLP 
technology makes learning an engaging and enjoyable experience, offering a dynamic and authentic way to master 
the Arabic language.</abstract>
		</paper>


