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| Élément Dublin Core | Valeur | Langue |
|---|---|---|
| dc.contributor.author | Aissaoui, Sonia | - |
| dc.contributor.author | Belhadjer, Samir | - |
| dc.date.accessioned | 2026-05-10T09:04:08Z | - |
| dc.date.available | 2026-05-10T09:04:08Z | - |
| dc.date.issued | 2020 | - |
| dc.identifier.uri | http://dspace.univ-bouira.dz:8080/jspui/handle/123456789/19755 | - |
| dc.description.abstract | Nowadays, text processing is a major field in machine learning that deals with the interaction between computers and humans using the natural language Predicting depression levels from social media is one of the most active research areas in natural language processing and text mining. This issue has many solutions offered with different classification techniques for machine learning. We hybridized two of the most known machine learning algorithms, convolutional neural network and long short-term memory to get better results. | en_US |
| dc.language.iso | fr | en_US |
| dc.publisher | AKLI MOHAND OULHADJ UNIVERSITY - BOUIRA | en_US |
| dc.subject | convolutional neural network, long short-term memory, machine learning, text processing, social media . . . | en_US |
| dc.title | Predicting Depression Levels Using Social Networking | en_US |
| dc.type | Thesis | en_US |
| Collection(s) : | Mémoires Master | |
Fichier(s) constituant ce document :
| Fichier | Description | Taille | Format | |
|---|---|---|---|---|
| .Aissaoui Sonia.pdf | 3,13 MB | Unknown | Voir/Ouvrir |
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