Výsledky vyhledávání - "Moustafa Al-Hajj"

LU-BZU at SemEval-2021 Task 2: Word2Vec and Lemma2Vec performance in Arabic Word-in-Context disambiguation

Publikováno v: SemEval@ACL/IJCNLP

This paper presents a set of experiments to evaluate and compare between the performance of using CBOW Word2Vec and Lemma2Vec models for Arabic Word-in-Context (WiC) disambiguation without using sense inventories or sense embeddings. As part of the S

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77d358a88642eb4642c66affc60abd04

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ArabGlossBERT: Fine-Tuning BERT on Context-Gloss Pairs for WSD

Autor: Mustafa Jarrar, Moustafa Al-Hajj

Publikováno v: RANLP

Using pre-trained transformer models such as BERT has proven to be effective in many NLP tasks. This paper presents our work to fine-tune BERT models for Arabic Word Sense Disambiguation (WSD). We treated the WSD task as a sentence-pair binary classi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc2761ccc06182acf9ffd41656de25ad
https://doi.org/10.26615/978-954-452-072-4_005

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Hybrid CNNs-LSTM Deep Analyzer for Arabic Opinion Mining

Autor: Amani Sabra, Nacereddine Hammami, Marwan Al Omari, Moustafa Al-Hajj

Publikováno v: SNAMS

Deep learning models have showed great capabilities in data modelling on natural language processing various applications, including sentiment analysis, part-of-speech tagging, machine translation, and many others. In particular, convolutional neural

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5e059b5cb3042a04f4da798a6a6d901b
https://doi.org/10.1109/snams.2019.8931819

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Sentiment Classifier: Logistic Regression for Arabic Services’ Reviews in Lebanon

Autor: Marwan Al Omari, Amani Sabra, Moustafa Al-Hajj, Nacereddine Hammami

Publikováno v: 2019 International Conference on Computer and Information Sciences (ICCIS).

This paper proposes a logistic regression approach paired with term and inverse document frequency (TF*IDF) for Arabic sentiment classification on services’ reviews in Lebanon country. Reviews are about public services, including hotels, restaurant

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https://doi.org/10.1109/iccisci.2019.8716394

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Use of Geomatic Approaches to Characterize Arqa River Basin: A Typical Coastal Lebanese River

Autor: Moustafa Al Hajj, Mhamad El Hage, Abdulrahim Ibrahim

Publikováno v: Open Journal of Modern Hydrology. :45-57

Water resources in Lebanon are one of the major threatened natural resources, since they spread on different geographic locations creating a network of permanent and temporary watercourses that govern the socio-economy and livelihood. However, lately

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https://doi.org/10.4236/ojmh.2015.53005

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Classifiers for Arabic NLP: survey

Autor: Moustafa Al-Hajj, Marwan Al Omari

Publikováno v: International Journal of Computational Complexity and Intelligent Algorithms. 1:231

In this paper, we reviewed most common-used models and classifiers that used for the Arabic language to classify texts into categories, classes, or topics in tasks of opinion mining, sentence categorisation, part of speech tagging, language identific

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https://doi.org/10.1504/ijccia.2020.105538

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Annotation Automatique Des Connaissances Spatiales En Arabe

Autor: Amani Sabra, Moustafa Al-Hajj, Rita Hijazi

Publikováno v: European Scientific Journal, ESJ. 14:218

In this paper, we introduce a rule-based approach to annotate Locative and Directional Expressions in Arabic natural language text. The annotation is based on a constructed semantic map of the spatiality domain. Challenges are twofold: first, we need

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8f41478c46e7bed5c1393577b2e6ce20
https://doi.org/10.19044/esj.2018.v14n14p218

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Extraction of reported speeches from Arabic Lebanese newspapers

Autor: Moustafa Al-Hajj, Ghassan Mourad

Publikováno v: DICTAP

This paper presents ongoing work on the extraction of Arabic reported speech, made by Lebanese politicians, from Arabic Lebanese newspapers. This work is part of a functional system for extraction, presentation and archiving of reported speech made b

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::226d256ed35efd30586541e8c15a21db
https://doi.org/10.1109/dictap.2015.7113184

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