Weighting based approach for learning resources recommendations

JOIV: International Journal on Informatics Visualization

Outmane Bourkoukou¹  Omar Achbarou¹ 

[1] Departement of computer science, Cadi Ayyad University, Marrakesh, 40000, Morocco

关键词: E-learning;    Recommender system;    Data sets;    Collaborative filtering;   

DOI  :  10.30630/joiv.2.3.124

学科分类：数学（综合）

来源: Politeknik Negeri Padang

【 摘 要 】

Personalized e-learning systems based on recommender systems refines enormous amount of data and provides suggestions on learning resources which is appealing to the learner. Although, the recommender systems depends on content based approach or collaborative filtering technique to make recommendations, these methods suffers from cold start and data sparsity problems. To overcome the limitations of the aforementioned problems, a weight based approach is proposed for better performance. The main criterion for building a personalized recommender system is to exploit useful content and provide better recommendations with minimal processing time. The proposed system is a web based client side application which uses user profiles to form neighborhoods and calculates predictions using weights. For newcomers a profile is constructed based on learning styles. The resources which might be of interest to the user are predicted from calculated predictions.

【 授权许可】

CC BY-SA