University Sétif 1 FERHAT ABBAS Faculty of Sciences
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Auteur chourouk Chaibedraa |
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Very Deep Attention-Based Models for Sentiments Analysis and Text Classification / abdenour Amine youcef
Titre : Very Deep Attention-Based Models for Sentiments Analysis and Text Classification Type de document : texte imprimé Auteurs : abdenour Amine youcef, Auteur ; chourouk Chaibedraa, Auteur ; Moussaou,iAbdelouahab, Directeur de thèse Année de publication : 2022 Importance : 1 vol (89 f .) Format : 29cm Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Natural language processing
Deep learningIndex. décimale : 004 Informatique Résumé :
Natural language processing is a field of study that focuses on building models that can
efficiently read, understand and generate human language.
Recently, With the rapid development of the Internet and its use in almost all areas, the
number of Internet users is increasing sharply. And As people surf the Internet, a large amount
of textual information is generated because text is still an important way for people to produce
and obtain information, hence the need for NLP techniques has increased, especially sentiment
classification which helps to understand people’s opinions and attitudes which is beneficial
in marketing activities, Brand Monitoring, Customer Service, Finance and Stock Monitoring,
Business Intelligence Buildup, Enhancing the Customer Experience, Market Research, and
Analysis.
This field has seen huge advances and progress in recent years to bring the best techniques
and deep learning models capable of better understanding and processing huge amounts of
textual data. The Attention mechanism and the Transformers play a role model, where recent
studies showed that they perform in all NLP tasks.
In this work, we’ll present a detailed study of recent advances in the field of deep learning
applied to natural language processing, mainly in the sentiment classification task. A total of 7
models were developed then trained and validated on 3 different datasets. The experiments show
that Transformer based models tend to perform better in the Sentiment classification task.Côte titre : MAI/0612 En ligne : https://drive.google.com/file/d/1varEKwQspEwadyxDln9SWry31QVBVz8j/view?usp=share [...] Format de la ressource électronique : Very Deep Attention-Based Models for Sentiments Analysis and Text Classification [texte imprimé] / abdenour Amine youcef, Auteur ; chourouk Chaibedraa, Auteur ; Moussaou,iAbdelouahab, Directeur de thèse . - 2022 . - 1 vol (89 f .) ; 29cm.
Langues : Français (fre)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Natural language processing
Deep learningIndex. décimale : 004 Informatique Résumé :
Natural language processing is a field of study that focuses on building models that can
efficiently read, understand and generate human language.
Recently, With the rapid development of the Internet and its use in almost all areas, the
number of Internet users is increasing sharply. And As people surf the Internet, a large amount
of textual information is generated because text is still an important way for people to produce
and obtain information, hence the need for NLP techniques has increased, especially sentiment
classification which helps to understand people’s opinions and attitudes which is beneficial
in marketing activities, Brand Monitoring, Customer Service, Finance and Stock Monitoring,
Business Intelligence Buildup, Enhancing the Customer Experience, Market Research, and
Analysis.
This field has seen huge advances and progress in recent years to bring the best techniques
and deep learning models capable of better understanding and processing huge amounts of
textual data. The Attention mechanism and the Transformers play a role model, where recent
studies showed that they perform in all NLP tasks.
In this work, we’ll present a detailed study of recent advances in the field of deep learning
applied to natural language processing, mainly in the sentiment classification task. A total of 7
models were developed then trained and validated on 3 different datasets. The experiments show
that Transformer based models tend to perform better in the Sentiment classification task.Côte titre : MAI/0612 En ligne : https://drive.google.com/file/d/1varEKwQspEwadyxDln9SWry31QVBVz8j/view?usp=share [...] Format de la ressource électronique : Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0612 MAI/0612 Mémoire Bibliothéque des sciences Anglais Disponible
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