International Journal of Academic Research in Computer Science and Electrical Engineering

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Volume 2, Issue 1 (Jan, 2015)

The Improvement of Electronic Learning’s Recommender Systems Performance
Author(s): Mahnaz Najafi, Fereshte Khoshnam, Sepide Jahangiri      Pages: [1-7]
Abstract

Today, the virtual environment is becoming more and more widespread as far as the control and processing of information is almost impossible. Therefore, the need for a system that can overcome this matter is felt more than ever. The systems that suggest the best and most friendly cases from among huge numbers of different products and data, according to the specific characteristics of each user, are very popular. The recommender systems are intelligent systems in the internet which identify the interests and preferences of users and offer relevant information to them. This study aimed to introduce recommender systems, analyze their techniques in detail, study the role of these systems in e-Learning to improve the learning of users in a virtual learning environment, and enhance the quality of recommendations with involvement of users’ information level in cooperative filtration algorithm to enhance the quality of users’ learning.

Keywords

E-Learning, User Profiles, Cooperative Filtration, Recommender Systems.

Full Text :PDF DOI: 10.6007/ijarcsee/v2-i1/1524