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1
A Sentiment analysis approach for Arabic dialects texts analysis based on automatic translation: Application to the Algerian dialect. ...
Guellil, Imane. - : Unpublished, 2021
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2
Sexism detection: The first corpus in Algerian dialect with a code-switching in Arabic/ French and English ...
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3
A semi-supervised approach for sentiment analysis of arab (ic+ izi) messages: Application to the algerian dialect
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4
Ara-Women-Hate: The first Arabic Hate Speech corpus regarding Women ...
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5
A Semi-supervised Approach for Sentiment Analysis of Arab(ic+izi) Messages: Application to the Algerian Dialect
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6
ArAutoSenti: automatic annotation and new tendencies for sentiment classification of Arabic messages [<Journal>]
Guellil, Imane [Verfasser]; Azouaou, Faical [Verfasser]; Chiclana, Francisco [Verfasser]
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7
ArAutoSenti: Automatic annotation and new tendencies for sentiment classification of Arabic messages
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8
Approche Hybride pour la translitération de l’arabizi algérien : une étude préliminaire
In: 25e conférence sur le Traitement Automatique des Langues Naturelles (TALN) ; https://hal.archives-ouvertes.fr/hal-01837234 ; 25e conférence sur le Traitement Automatique des Langues Naturelles (TALN), May 2018, Rennes, France (2018)
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9
Hybrid approach for transliteration of Algerian arabizi: a primary study ...
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10
SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis
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11
SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis ...
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12
Comparison between Neural and Statistical translation after transliteration of Algerian Arabic Dialect
In: WiNLP: Women & Underrepresented Minorities in Natural Language Processing (co-located withACL 2017) ; https://hal.archives-ouvertes.fr/hal-01570298 ; WiNLP: Women & Underrepresented Minorities in Natural Language Processing (co-located withACL 2017), Jul 2017, Vancouver, Canada ; http://www.winlp.org/winlp-workshop (2017)
Abstract: International audience ; Research on Arabic Dialect Treatment has recently become important in the literature. Although most work on these dialects considers only the messages or the portion of text written in Arabic letters, another style of writing has emerged on social media. This style is known by Arabizi and combines between Latin letters and numbers. To address this emergent problem in the context of automatic translation, we present an Arabic dialect translation system composed by two modules: Transliteration and translation. We develop each module with a statistical and a neural model. To test our system, we used the Algerian portion of a multi-dialectal Arabic corpus named PADIC. Experimental results show that a good transliteration improves the translation results. Moreover, the neural transliteration gives better results than the statistical transliteration. However, the statistical translation still gives better results that the neural translation.
Keyword: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]; Algerian Dialect; Arabic Dialect; Arabizi; Neural translation; Neural transliteration; Statistical translation; Statistical transliteration
URL: https://hal.archives-ouvertes.fr/hal-01570298
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