University Sétif 1 FERHAT ABBAS Faculty of Sciences
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Auteur Guettaf, Amina |
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Titre : Subjectivity and Sentement Analysis in Arabic Text Type de document : texte imprimé Auteurs : Guettaf, Amina, Auteur ; Sadik Bessou, Directeur de thèse Editeur : Setif:UFA Année de publication : 2021 Importance : 1 vol (47 f .) Format : 29 cm Langues : Anglais (eng) Catégories : Thèses & Mémoires:Informatique Mots-clés : Subjectivity and sentiment analysis
Machine learningIndex. décimale : 004 - Informatique Résumé :
The task of subjectivity and sentiment analysis is commonly defined as classifying a
given text into one of two classes: objective or subjective. It’s often used by businesses
to detect sentiment in social data, gauge brand reputation, and understand customers.
SSA is becoming an essential tool to monitor and understand the customers thoughts
and feelings more openly than ever. Automatically analyzing customer feedback, such as
opinions in survey responses and social media conversations, allows brands to learn what
makes customers happy or frustrated, so that they can tailor products and services to
meet their customers needs. In this work, the purpose is to achieve a particular accuracy
using different natural language processing approaches and machine learning techniques
in a collection of tweets written in Arabic dialect and Modern Standard Arabic.Côte titre : MAI/0555 En ligne : https://drive.google.com/file/d/1Y34aur8OoenlxB9H6-HR2GKoR7vcOxjy/view?usp=shari [...] Format de la ressource électronique : Subjectivity and Sentement Analysis in Arabic Text [texte imprimé] / Guettaf, Amina, Auteur ; Sadik Bessou, Directeur de thèse . - [S.l.] : Setif:UFA, 2021 . - 1 vol (47 f .) ; 29 cm.
Langues : Anglais (eng)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Subjectivity and sentiment analysis
Machine learningIndex. décimale : 004 - Informatique Résumé :
The task of subjectivity and sentiment analysis is commonly defined as classifying a
given text into one of two classes: objective or subjective. It’s often used by businesses
to detect sentiment in social data, gauge brand reputation, and understand customers.
SSA is becoming an essential tool to monitor and understand the customers thoughts
and feelings more openly than ever. Automatically analyzing customer feedback, such as
opinions in survey responses and social media conversations, allows brands to learn what
makes customers happy or frustrated, so that they can tailor products and services to
meet their customers needs. In this work, the purpose is to achieve a particular accuracy
using different natural language processing approaches and machine learning techniques
in a collection of tweets written in Arabic dialect and Modern Standard Arabic.Côte titre : MAI/0555 En ligne : https://drive.google.com/file/d/1Y34aur8OoenlxB9H6-HR2GKoR7vcOxjy/view?usp=shari [...] Format de la ressource électronique : Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0555 MAI/0555 Mémoire Bibliothéque des sciences Anglais Disponible
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