Content Based Recommender System Using Deep Leaning / Lynda Messah  

Public ISBD Titre : Content Based Recommender System Using Deep Leaning Type de document : texte imprimé Auteurs : Lynda Messah, Auteur ; Chahrazed Bendaas, Auteur ; Mediani,Chahrazed, Directeur de thèse Année de publication : 2022 Importance : 1 vol (73 f .) Format : 29cm Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Recommender system content-based Index. décimale : 004 Informatique Résumé : Recommender systems have the effect of leading users to interesting objects in a vast universe of available possibilities in a personalized way. Content-based recommendation systems try to suggest items that are relevant to those that a user has previously enjoyed. Indeed, a content-based recommender’s basic process requires combining the properties of a user profile, which stores preferences and interests, with the attributes of a content object (item), to suggest new interesting items to the user. In this thesis, we presented a new approach to a recommendation based on content using deep learning to provide problems related to avoid traditional approaches while improving system quality and performance. Côte titre : MAI/0609 En ligne : https://drive.google.com/file/d/17Ab3XkrA_UcDP_v8ndr5uOZDVR4gmln2/view?usp=share [...] Format de la ressource électronique : pdf Content Based Recommender System Using Deep Leaning [texte imprimé] / Lynda Messah, Auteur ; Chahrazed Bendaas, Auteur ; Mediani,Chahrazed, Directeur de thèse . - 2022 . - 1 vol (73 f .) ; 29cm. Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Recommender system content-based Index. décimale : 004 Informatique Résumé : Recommender systems have the effect of leading users to interesting objects in a vast universe of available possibilities in a personalized way. Content-based recommendation systems try to suggest items that are relevant to those that a user has previously enjoyed. Indeed, a content-based recommender’s basic process requires combining the properties of a user profile, which stores preferences and interests, with the attributes of a content object (item), to suggest new interesting items to the user. In this thesis, we presented a new approach to a recommendation based on content using deep learning to provide problems related to avoid traditional approaches while improving system quality and performance. Côte titre : MAI/0609 En ligne : https://drive.google.com/file/d/17Ab3XkrA_UcDP_v8ndr5uOZDVR4gmln2/view?usp=share [...] Format de la ressource électronique : pdf

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
MAI/0609	MAI/0609	Mémoire	Bibliothéque des sciences	Anglais	Disponible Disponible

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