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An Automatic Definition Extraction in Arabic Language [chapter]

Omar Trigui, Lamia Hadrich Belguith, Paolo Rosso
2010 Lecture Notes in Computer Science  
We propose a method based on patterns to automatically identify a definition answer to a definition question. The proposed method is implemented in an Arabic definitional question answering system.  ...  In this paper, we tackle the automatic definition extraction in the context of Question Answering systems.  ...  The work of the third author was carried out in the framework of the AECID-PCI C/026728/09 and the TIN2009-13391-C04-03 research projects. An Automatic Definition Extraction in Arabic Language  ... 
doi:10.1007/978-3-642-13881-2_25 fatcat:rrzldgiu5ngx5enkat232qsnvy

Towards a New Hybrid Approach for Abstractive Summarization

Younes Jaafar, Karim Bouzoubaa
2018 Procedia Computer Science  
We firstly begin with an extractive step to keep only sentences with high weights.  ...  The Arabic community has focused mainly on extractive techniques rather than abstractive ones. In this article, we present a new approach for abstractive summarization using conceptual graphs (CGs).  ...  The "Ikhtasir" system [8] is an automatic extractive Arabic text summarization system.  ... 
doi:10.1016/j.procs.2018.10.496 fatcat:57d2e6srgjesje7craxxl5avle

Constructing a corpus-informed list of Arabic formulaic sequences (ArFSs) for language pedagogy and technology

Ayman Alghamdi, Eric Steven Atwell
2019 International Journal of Corpus Linguistics  
This study aims to construct a corpus-informed list of Arabic Formulaic Sequences (ArFSs) for use in language pedagogy (LP) and Natural Language Processing (NLP) applications.  ...  A hybrid mixed methods model was adopted for extracting ArFSs from a corpus, that combined automatic and manual extracting methods, based on well-established quantitative and qualitative criteria that  ...  This paper extends our earlier work on ArFSs reported in , (Alghamdi & Atwell, 2017) . Notes 1. The German standard DIN 31636 is used for rendering Romanized Arabic as described in the Appendix.  ... 
doi:10.1075/ijcl.16088.alg fatcat:xfcoi22emvewnoumc3u7uwkyry

An Ontology-based Name Entity Recognition NER and NLP Systems in Arabic Storytelling

Marwa Elgamal, Mohamed Abou-Kreisha, Reda Abo Elezz, Salwa Hamada
2020 Al-Azhar Bulletin of Science  
In this work, a practical methodology presented for Arabic Storytelling ontology construction for domain ontology extraction from unstructured Arabic story documents.  ...  This paper intends to investigate the problem of automatically construct and build an Arabic storytelling ontology based on Arabic named entity recognition (NER) from unstructured story text.  ...  In the Arabic Language.  ... 
doi:10.21608/absb.2020.44367.1088 fatcat:al6yof2kozajvot77cta2globe

Survey and Classification of Methods for Building a Semantic Annotation

Georges Lebbos, Abd El, Gilles Bernard, Mohammad Hajjar
2017 International Journal of Advanced Computer Science and Applications  
This work should contribute to the definition of new methods and help researchers on Arabic semantics to fit their work in the panel of existing ones.  ...  Though Arabic is one of the five most spoken languages, little work has been done on building Arabic semantic resources.  ...  In addition, the module allows the automatic extraction of SUMO concepts definitions written in SUO-KIF notation. E.  ... 
doi:10.14569/ijacsa.2017.081264 fatcat:3dciypdtkveq7dni2yax625bqe

AQA-WebCorp: Web-based Factual Questions for Arabic

Wided Bakari, Patrice Bellot, Mahmoud Neji
2016 Procedia Computer Science  
As well as, Arabic doesn't have an equivalent number of linguistic corpuses as compared to other languages like English. In this paper, we focus on building our corpus of Arab questions-texts.  ...  This method is based on a real automatic interrogation of Google, in order to generate passages of texts and answer the factual questions.  ...  This stage is an essential step in achieving most applications in automatic language processing.  ... 
doi:10.1016/j.procs.2016.08.140 fatcat:xch53oyze5hj3g36vtslct2kzu

Arabic Cooperative Answer Generation via Wikipedia Article Infoboxes

Omar Trigui. Lamia Hadrich Belguith, Paolo Rosso
2017 Research in Computing Science  
We have chosen to integrate and experiment it in a definitional question-answering system dealing with the Arabic language entitled DefArabicQA.  ...  These challenges increase when the requested answer is cooperative and its language is Arabic.  ...  We have used a dataset comprising 300 definition questions in the Arabic language. The questioner is an adult, a native speaker of Arabic, and a reader of Arabic newspapers.  ... 
doi:10.13053/rcs-132-1-11 fatcat:xawmgd2xlbhoxcbakpbo4tdume

Azhary: An Arabic Lexical Ontology

Hossam Ishkewy, Hany Harb, Hassan Farahat
2014 International journal of Web & Semantic Technology  
Arabic language is the most spoken languages in the Semitic languages group, and one of the most common languages in the world spoken by more than 422 million.  ...  Arabic is also a major ritual language of a number of Christian churches in the Arab world and it is also used in writing several intellectual and religious Jewish books in the Middle Ages.  ...  The second is using an automatic extraction algorithm to extract new concepts from linguistic texts to enrich the ontology.  ... 
doi:10.5121/ijwest.2014.5405 fatcat:o2ced7jdyzgq5a52umosm6wmzq

Towards an Arabic Web-based Information Retrieval System (ARABIRS): Stemming to Indexing

El YounoussiYacine
2015 International Journal of Computer Applications  
Arabic, the mother tongue of over 300 million people around the world, is known as one of the most difficult languages in Automatic Natural Language processing (NLP) in general and information retrieval  ...  In this context, we dared to focus all our researches to implement an Arabic web-based information retrieval system entitled ARABIRS (ARABic Information Retrieval System).  ...  We then applied our automatic stems extraction approach on the definitions of all the test roots.  ... 
doi:10.5120/19257-1009 fatcat:tlkqmehlsjckbn5qviwod6b7vu

Extracting Synonyms from Bilingual Dictionaries [article]

Mustafa Jarrar, Eman Karajah, Muhammad Khalifa, Khaled Shaalan
2020 arXiv   pre-print
We compared the original and extracted synsets obtaining an F-Measure of 82.3% and 82.1% for Arabic and English synsets extraction, respectively.  ...  The initial evaluation of this algorithm illustrates promising results in extracting Arabic-English bilingual synonyms.  ...  Figure 1 illustrates an Arabic-English translation graph extracted from the Arabic WordNet.  ... 
arXiv:2012.00600v1 fatcat:qlnz4ab7tzgpvhybr6ssjnzl7y

A Comparative Study on Arabic Stemmers

Mohamed Y., Asma'a Al, Rihab Al-Mutawa
2015 International Journal of Computer Applications  
The Arabic language has many special cases or properties that affect stemming or any automatic method, it depends on both inflectional and derivational morphology to produce the various forms of the language  ...  Stemming is considered as a pre-processing step in many applications: text mining, information retrieval, machine translation etc.  ...  Arabic stemming is an approach that goes after finding the origin of words in the natural Arabic language by removing any additional (affixes) in the words [26] .  ... 
doi:10.5120/ijca2015906129 fatcat:57ckgr5wuvavpn3qd4d773cavq


O. El Barbary
2018 Journal of the Egyptian Mathematical Society  
Arabic language is still facing some difficulties in automatic processing relating to the richness, morphology, phonetic and lexicon.  ...  The advantage of our approach is to build an extended and updated automatic Arabic morphological field dictionary.  ...  Arabic morphology All previous studies are based on FA words in English and Japanese, and the extension of FA words to another language such Arabic could be definitely strengthened further researches.  ... 
doi:10.21608/joems.2018.2984.1053 fatcat:edrhnequdrgx3bp7mfwwjwvpzu

Building Ontology from Texts

Bedr-eddine Benaissa, Djelloul Bouchiha, Amine Zouaoui, Noureddine Doumi
2015 Procedia Computer Science  
The purpose of this paper is to present an approach to create semi-automatically ontology from Arabic texts. The whole process is supervised by a linguistic expert.  ...  Our involvement in this project focused on a lexical ontology, taking as model the WordNet ontology, and as input source, the "Arabic verbs" of a contemporary monolingual dictionary ( ) /m jm Al ny/ in  ...  Benaissa Tedjini, Professor in Arabic linguistics at the University of Abu Bakr Belkaid -Tlemcen, ALGERIA, for the fruitful discussions about the syntax of Arabic sentences and their morphosyntactic analysis  ... 
doi:10.1016/j.procs.2015.12.042 fatcat:2g5lxskgaza6jaxv7vd7x6nffa

Semantic Annotation of Arabic Web Resources Using Semantic Web Services

Saeed Albukhitan, Ahmed Alnazer, Tarek Helmy
2016 Procedia Computer Science  
Since Arabic language received less attention in semantic Web research as compared to Latin languages especially in the field of semantic annotation.  ...  This motivates us in this paper to present semantic Web services that support the semantic annotation of Arabic language documents.  ...  In addition, the authors would like to thank both conference Chairs and the anonymous reviewer's for their valuable comments that enhance the paper presentation.  ... 
doi:10.1016/j.procs.2016.04.243 fatcat:btdzmq46q5b2xdxgjrquv4hcvm

Leveraging Linked Open Data to Automatically Answer Arabic Questions

Mohammad AL-Smadi, Islam AL-Dalabih, Yaser Jararweh, Patrick JUOLA
2019 IEEE Access  
This research targets an important, yet insufficiently precedent, area in using Linked Open Data (LOD) for Automatic Question Answering systems in the Arabic Language.  ...  To evaluate our proposed system, an Arabic questions dataset was created including: (a) Question body in Arabic language, (b) Question type, (c) SPARQL Query formulation, and (d) Question answer.  ...  LOD in automatically answering different types of Arabic questions presented in natural language.  ... 
doi:10.1109/access.2019.2956233 fatcat:s752k2s2k5gwxahk5vf56h6ozq
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