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Please use this identifier to cite or link to this item: https://repository.esi-sba.dz/jspui/handle/123456789/257
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dc.contributor.authorALAHOUM, NAdjia-
dc.contributor.authorKOUADRI, AIchouch RAnia-
dc.date.accessioned2022-04-20T13:31:00Z-
dc.date.available2022-04-20T13:31:00Z-
dc.date.issued2021-
dc.identifier.urihttps://repository.esi-sba.dz/jspui/handle/123456789/257-
dc.descriptionPr. Sidi Mohamed BENSLIMANE Encadreur Dr. Badia KLOUCHE Co-Encadreuren_US
dc.description.abstractSentiment analysis, also known as Opinion Mining, is a subfield of natural language processing. Since humans are omnipresent in today’s ultra-connected world thanks to social networks, they are constantly expressing their opinions on multiple topics in a multitude of occasions. Sentiment analysis is therefore crucial to identify the user’s opinion and interests. When the user is native of the Arabic world, things are not different, on the contrary, the richness and diversity of Arabic dialects makes social networks full of opinions. It is therefore wise to try to exploit this mass of information to extract useful information. In this work, we focus on the sentiment analysis of Arabic dialects (focal point on the Algerian dialect), in order to make a state of the art inventory of the different approaches and techniques useden_US
dc.language.isofren_US
dc.subjectSentiment Analysisen_US
dc.subjectOpinion Miningen_US
dc.subjectNLPen_US
dc.subjectArabic Dialecten_US
dc.subjectDeep Learningen_US
dc.subjectMachine Learningen_US
dc.subjectClassification Modelsen_US
dc.titleAnalyse des sentiments Appliquée aux dialectes arabesen_US
dc.typeThesisen_US
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