Arabic Language Processing: From Theory to Practice

This two-volume set, CCIS 2339 and CCIS 2340, constitutes the refereed proceedings of the 8th International Conference on Arabic Language Processing, ICALP 2023, held in Rabat, Morocco, during April 1920, 2024.

The 30 full papers and 11 short papers presented in these two volumes were carefully reviewed and selected from 107 submissions.

The papers are organized in the following topical sections:

Part I: Learning Arabic and dialectal and Sentiment Analysis; Advancements in Deep Learning for Arabic Language Processing: Generation, Translation, and QA.

Part II: Linguistic Resources for Arabic NLP; Various analysis of Arabic.

Inhalt

.- Learning Arabic and dialectal and Sentiment Analysis.

.- Sentiment Analysis on Moroccan Dialect of Arabic combining NLP and ML methods.

.- Enhancing Arabic Sentiment Analysis using Arabic LLMs.

.- Sentiment analysis of texts written in Arabic: Addressing the issue of negation.

.- Automatic Arabic Essays Scoring: A Scoping Review.

.- Bridging the Emotional Gap: Google NL-AI Sentiment Analysis in Comparing Moroccan Literary Translations.

.- HateTune: Tunisian Dialect Hate Speech Detection Dataset.

.- DarijaGenie: Learning Moroccan Arabic Through a Multimodal Chatbot.

.- Morpho-lexical based approach for Arabic WorldNet extension.

.- A Hybrid Annotation Model for Arabic Argumentative Debate Corpus.

.- Alkhalil Platform for Arabic Language Processing.

.- Advancements in Deep Learning for Arabic Language Processing : Generation, Translation, and QA.

.- Exploring semantic Hadith Overlap across Topics.

.- Stance Detection in Arabic Dialects: Preliminary Experiments.

.- MAGENTA: Generating and Detecting Arabic Machine-Generated Text in Multiple Domains.

.- Transformers and Spark for Automated CV Classification in Arabophone regions.

.- Fine-Tuning AraBART on AHS dataset for Arabic Abstractive Summarization.

.- Qur'an Passage Ranking Using Transformer Models.

.- Question Answering Over the Arabic Hadith Sharif Using Transformer Models.

.- Deep Reinforcement Learning for Arabic Machine Translation: A Study on Reward Signals.

.- ARAP-IRONY: a Multi-dialectal Arabic Irony Corpus for Irony Detection.

.- Context-aware Arabic Diacritization using Transformers.

.- Classifying Persuasion Modes in Arabic Debates: A Preliminary Language Model-based Analysis.

.- Strengthening deep learning through morphological analysis for an Arabic Lemmatizer development.

.- Enhancing Arabic Word Sense Disambiguation with Ensemble BERT-based Models.