@conference {Trabelsi2021281,
	title = {Hybrid Recommendation Systems: A State of Art},
	booktitle = {International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE - Proceedings},
	volume = {2021-April},
	year = {2021},
	note = {cited By 0},
	pages = {281-288},
	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 {\textcopyright} 2021 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved},
	keywords = {Application area, Collaborative filtering, Content based filtering, E- commerces, Hybrid filtering, Hybrid recommendation, Literature reviews, Recommendation problem, Recommender Systems, State of art, System use},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137960955\&partnerID=40\&md5=eae4312d0264db7b508c80e8414023e3},
	author = {Trabelsi, F.Z. and Khtira, A. and El Asri, B.}
}
