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Hybrid deep learning models for fake news detection: case study on Arabic and English languages. [PDF]
Front Big DataMerzah BM, Razmara J, Salmanian Z.
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Cognitive salience features enhance multitask deep learning for pragmatic reasoning across cultures. [PDF]
Sci RepQi M.
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Arabic Natural Language Processing
ACM Transactions on Asian Language Information Processing, 2009The Arabic language presents researchers and developers of natural language processing (NLP) applications for Arabic text and speech with serious challenges. The purpose of this article is to describe some of these challenges and to present some solutions that would guide current and future practitioners in the field of Arabic natural language ...
Khaled Shaalan
exaly +2 more sources
The Use of Hidden Markov Model in Natural ARABIC Language Processing: a survey
Procedia Computer Science, 2017 Abstract Hidden Markov Model is an empirical tool that can be used in many applications related to natural language processing. In this paper a comparative study was conducted between different applications in natural Arabic language processing that uses Hidden Markov Model such as morphological analysis, part of speech tagging, text classification ...
Arafat Awajan
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Using natural language processing for analyzing Arabic poetry rhythm
2017 16th RoEduNet Conference: Networking in Education and Research (RoEduNet), 2017One from the most difficult tasks for Natural Language Processing (NLP) is to analyze poetry, which uses a different genre of language than that considered by computer-based techniques. Therefore, computational analysis is an interesting task when we use NLP in poetry, but it is also challenging.
Stefan Trausan-Matu
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Natural Language Processing for Arabic Metaphors: A Conceptual Approach
2016Metaphor is a literary device that allows us to express a concept in terms of another. In other words, it is based on similarity between concepts. Metaphorical expressions represent a great variety and they are used in conventional metaphors, which we reproduce and comprehend every day, poetic, novel, and Holy Qur’an.
Manar Alkhatib, Khaled Shaalan
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ARBML: Democratizing Arabic Natural Language Processing Tools
Proceedings of Second Workshop for NLP Open Source Software (NLP-OSS), 2020Automating natural language understanding is a lifelong quest addressed for decades. With the help of advances in machine learning and particularly, deep learning, we are able to produce state of the art models that can imitate human interactions with languages.
Zaid Alyafeai, Maged S. Al-Shaibani
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Text Classification in Arabic Natural Language Processing: A Review
2023 3rd International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2023Hana Al-Hadheri +2 more
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