DSpace Repository

MORES : A Movie Recommendation System

Show simple item record

dc.contributor.author Adjali, Naziha Fatma
dc.contributor.author Akrouche, Wassila
dc.contributor.author El Bouhissi, Houda ; promotrice
dc.date.accessioned 2021-02-01T10:51:10Z
dc.date.available 2021-02-01T10:51:10Z
dc.date.issued 2020
dc.identifier.uri http://hdl.handle.net/123456789/14097
dc.description Option : software engineering en_US
dc.description.abstract With the increasing amount of data content produced daily, it becomes very di?cult for users to ?nd the resources suitable to their needs. Recommendation systems are proposed to solve this problem and are capable of providing personalized recommendations or guiding the user to interesting or useful resources within a large data space. Recently, Recommender systems are getting importance due to their signi?cance in making decisions and providing detailed information about the required product or a service. In this paper, we conduct a systematic review for recommendation models, and discuss the challenges and open issues. Furthermore, we propose a new recommendation system ontology-based in which machine-learning algorithms are used to achieve user needs identi?cation and provide precise recommendations. en_US
dc.language.iso en en_US
dc.publisher université Abderrahmane Mira- Bejaia en_US
dc.subject MORES : Recommendation systems : Advantage : Typology : Semantic web : ML en_US
dc.title MORES : A Movie Recommendation System en_US
dc.type Thesis en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account