Results 1 to 10 of about 1,363 (163)
Dialectal substitution as an adversarial approach for evaluating Arabic NLP robustness [PDF]
Scientific ReportsRecent advances in deep neural networks (DNNs) have led to significant enhancements in Arabic natural language processing (NLP). However, their robustness remains insufficiently explored, particularly in adversarial settings.
Basemah Alshemali
doaj +5 more sources
AraVec: A set of Arabic Word Embedding Models for use in Arabic NLP
Procedia Computer Science, 2017 Abstract Advancements in neural networks have led to developments in fields like computer vision, speech recognition and natural language processing (NLP). One of the most influential recent developments in NLP is the use of word embeddings, where words are represented as vectors in a continuous space, capturing many syntactic and semantic relations ...
Samhaa R El-Beltagy
exaly +2 more sources
Legal case documents: A comprehensive dataset for Arabic natural language processing research and applicationsKaggle [PDF]
Data in BriefThe legal sector remains distinctive due to the complex language structure and specialized terminology of legal data. This complexity offers considerable contextual information, which demands natural language processing (NLP).
Soha Zarbah, Arwa Wali, Dimah Alahmadi
doaj +2 more sources
Graph-based Arabic NLP Techniques: A Survey
Procedia Computer Science, 2018 Abstract The improvements of natural language processing applications such as machine translation, text summarization and the likes are crucial, and can be achieved using many different techniques including graph, deep learning, word embedding and others.
Arafat Awajan, Wael Etaiwi
exaly +2 more sources
ComputersArabic natural language processing (NLP) has garnered significant attention in recent years due to the growing demand for automated text and Arabic-based intelligent systems, in addition to digital transformation in the Arab world.
Abdulaziz Alayba
exaly +3 more sources
Big Data and Cognitive ComputingRecent studies have highlighted the growing integration of Natural Language Processing (NLP) techniques and Large Language Models (LLMs) in healthcare. These technologies have shown promising outcomes across various healthcare tasks, especially in widely
Ömer S Alkhnbashi +2 more
exaly +3 more sources
A comparative study of Arabic syntactic analyzers [PDF]
Frontiers in Artificial IntelligenceSyntactic analysis stands at the heart of Natural Language Processing (NLP), serving as the cornerstone upon which deeper linguistic understanding is built—particularly for morphologically complex languages such as Arabic.
Omar Saadiyeh +3 more
doaj +2 more sources
Arab2Vec: An Arabic word embedding model for use in Twitter NLP applications. [PDF]
PLoS OneThe analysis of Arabic Twitter data sets is a highly active research topic, particularly since the outbreak of COVID-19 and subsequent attempts to understand public sentiment related to the pandemic. This activity is partially driven by the high number of Arabic Twitter users, around 164 million.
Hamdy A, Youssef A, Ryan C.
europepmc +3 more sources
Classifiers for Arabic NLP: survey
International Journal of Computational Complexity and Intelligent Algorithms, 2020 Marwan Al Omari, Moustafa Al Hajj
exaly +2 more sources
Constructing and evaluating ArabicStanceX: a social media dataset for Arabic stance detection [PDF]
Frontiers in Artificial IntelligenceArabic stance detection has attracted significant interest due to the growing importance of social media in shaping public opinion. However, the lack of comprehensive datasets has limited research progress in Arabic Natural Language Processing (NLP).
Ali Alkhathlan +3 more
doaj +2 more sources