Results 11 to 20 of about 1,363 (163)

Open source Arabic research paper dataset for natural language processing [PDF]

open access: yesScientific Reports
Recent advancements in applications such as natural language processing (NLP), applied linguistics, indexing, data mining, information retrieval, and machine translation have emphasized the need for robust datasets and corpora.
Tahani M. Almutairi   +3 more
doaj   +2 more sources

Unveiling Arabic named entity recognition using natural language processing with artificial intelligence approach on Moroccan dialect [PDF]

open access: yesScientific Reports
Named entity recognition (NER) is a significant natural language processing task (NLP) in several applications, including question-answering and data retrieval.
Wala Bin Subait   +7 more
doaj   +2 more sources

Advancing arabic dialect detection with hybrid stacked transformer models [PDF]

open access: yesFrontiers in Human Neuroscience
The rapid expansion of dialectally unique Arabic material on social media and the internet highlights how important it is to categorize dialects accurately to maximize a variety of Natural Language Processing (NLP) applications.
Hager Saleh   +8 more
doaj   +2 more sources

Within-Document Arabic Event Coreference: Challenges, Datasets, Approaches and Future Direction

open access: yesApplied Sciences, 2023
Event coreference resolution is a crucial component in Natural Language Processing (NLP) applications as it directly affects text summarization, machine translation, classification, and textual entailment.
Mohammed Aldawsari   +2 more
doaj   +1 more source

Lexical and Morphological Statistics of an Arabic POS-Tagged Corpus [PDF]

open access: yesThe Egyptian Journal of Language Engineering, 2014
Part-Of-Speech (POS) tagging is a basic component necessary for many Natural Language Processing (NLP) applications. Building a manually tagged corpus helps in studying key statistics of a given language which form the basis for POS tagging systems.
Hamdy Mubarak   +2 more
doaj   +1 more source

GPTAraEval: A Comprehensive Evaluation of ChatGPT on Arabic NLP

open access: yesProceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
EMNLP 2023 Main ...
Md. Tawkat Islam Khondaker   +3 more
openaire   +2 more sources

ZCU-NLP at MADAR 2019: Recognizing Arabic Dialects [PDF]

open access: yesProceedings of the Fourth Arabic Natural Language Processing Workshop, 2019
In this paper, we present our systems for the MADAR Shared Task: Arabic Fine-Grained Dialect Identification. The shared task consists of two subtasks. The goal of Subtask– 1 (S-1) is to detect an Arabic city dialect in a given text and the goal of Subtask–2 (S-2) is to predict the country of origin of a Twitter user by using tweets posted by the user ...
Pavel Pribán, Stephen Taylor 0001
openaire   +1 more source

The Effectiveness of Arabic Stemmers Using Arabized Word Removal

open access: yesInternational Journal of Information Science and Management, 2022
Other languages have influenced Arabic because of several factors, such as geographical nearness, trade communication, past Islamic conquests, science and technology, new devices, brand names, models, and fashion.
Hamood ALshalabi   +4 more
doaj  

Leveraging Arabic sentiment classification using an enhanced CNN-LSTM approach and effective Arabic text preparation

open access: yesJournal of King Saud University: Computer and Information Sciences, 2022
The high variety in the forms of the Arabic words creates significant complexity related challenges in Natural Language Processing (NLP) tasks for Arabic text.
Abdulaziz M. Alayba, Vasile Palade
doaj   +1 more source

AraScore: A deep learning-based system for Arabic short answer scoring

open access: yesArray, 2022
In the past years, Arabic NLP has been significantly lagging behind its English counterpart, but recent advancements in Natural Language Processing have made it possible for Arabic to catch up and show promising results for a multitude of tasks.
Omar Nael   +2 more
doaj   +1 more source

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