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