المجلة الجزائرية للعلوم
Volume 7, Numéro 14, Pages 36-40
2021-06-03
Contextual Collaborative Filtering Recommandations Using Bio‐ Inspired Algorithm
Authors : Btissem Gasmi . Hassina Seridi-bouchelaghem . Fouzia Anguel .
Abstract
Collaborative filtering algorithm has been successfully employed in e-commercial and academic application. However, traditional collaborative filtering methods use only users’ evaluations and do not consider the change of the users’ preferences over context. They give a same treatment on user’s score in different contextual situations. In order to solve above problem, this paper proposes a new item-based collaborative filtering algorithm in order to incorporate contextual information of users and items. The proposed algorithm endows the rating of a user on an item with a weight function which takes into account the importance of each contextual information for users. Experimental results from Movielens data set show that the proposed algorithm outperforms the traditional item- based collaborative filtering algorithm.
Keywords
Recommender system, Collaborative filtering, Contextual information Genetic algorithm, Movielens
Les articles similaires
Abderrahmane Gaham
.
Ahlem Melouah
.
Mohamed Amine Yakoubi
.
pages 95-102.
Khellat Kihel Badra
.
Chouraqui Samira
.
pages 36-43.
Benhammou Aissa
.
Hartani Mohamed Amine
.
Kimi Imade Eddine
.
Soumeur Mohammed Amine
.
Baba Mohammed
.
pages 26-32.
Youbi Karima
.
Kechroud Bachir
.
pages 100-122.
Sellam Rachid
.
Djeddi Mabrouk
.
Aitouche Mohand Amokrane
.
Djeddi Mounir
.
pages 189-203.
