Hybrid Recommendation Systems: A State of Art

Titre	Hybrid Recommendation Systems: A State of Art
Publication Type	Conference Paper
Year of Publication	2021
Authors	Trabelsi, FZ, Khtira, A, B. Asri, E
Conference Name	International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE - Proceedings
Mots-clés	Application area, Collaborative filtering, Content based filtering, E- commerces, Hybrid filtering, Hybrid recommendation, Literature reviews, Recommendation problem, Recommender Systems, State of art, System use
Abstract	Recommendation systems have become more important and popular in many application areas such as music, movies, e-commerce, advertisement and social networks. Recommendation systems use either collaborative filtering, content-based filtering or hybrid filtering in order to propose items to users, and each type has its weaknesses and strengths. In this paper, we present the results of a literature review that focuses specifically on hybrid recommendation systems. The objective of this review is to identify the problems that hybrid filtering tends to solve and the different techniques used to this end. Copyright © 2021 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved
URL	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137960955&partnerID=40&md5=eae4312d0264db7b508c80e8414023e3