E-learning με χρήση recommendation συστημάτων

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Εκπαίδευση από απόσταση ; Διαδίκτυο (Internet) στην εκπαίδευση ; Recommender systems (Information filtering) ; Personal communication service systemsAbstract
Recommender systems are widely used in many areas, especially in ecommerce. Recently, they are also applied in e-learning for recommending learning objects to students - users. Recommender systems apply knowledge discovery techniques to the problem of making personalized product recommendations during a live customer interaction. These systems, especially the k-nearest neighbor and collaborative filtering based ones, are achieving widespread success in E-commerce and e-learning. The goal of a Recommender System is to generate meaningful recommendations to a collection of users for items or products or education data that might interest them. This paper aims to study problems of both systems that contain “hidden knowledge” and e-learning applications and focuses on improving the quality and the efficiency of services provided to end users. At first we study the problem of producing recommendations using an e-learning platform. The proposed hybrid approach aims to produce effective recommendations for potential users of an online e-learning application. The knowledge for the users and the products are derived from usage data, educational level, specialty, age, language skills, courses, age of registered users.