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dc.contributor.authorAissaoui, Sonia-
dc.contributor.authorBelhadjer, Samir-
dc.date.accessioned2026-05-10T09:04:08Z-
dc.date.available2026-05-10T09:04:08Z-
dc.date.issued2020-
dc.identifier.urihttp://dspace.univ-bouira.dz:8080/jspui/handle/123456789/19755-
dc.description.abstractNowadays, 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.isofren_US
dc.publisherAKLI MOHAND OULHADJ UNIVERSITY - BOUIRAen_US
dc.subjectconvolutional neural network, long short-term memory, machine learning, text processing, social media . . .en_US
dc.titlePredicting Depression Levels Using Social Networkingen_US
dc.typeThesisen_US
Collection(s) :Mémoires Master

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