This article presents research on personal recommender systems for lifelong learning. The personal recommender systems supports lifelong learners in Learning Networks. A first version was evaluated in an experiment during an Introduction Psychology course of the Psychology Department at the Open University of the Nederlands. The learning activities of the psychology course and the personal reco...

Memory-based collaborative filtering is the most popular approach to build recommender systems. Despite its success in many applications, it still suffers from several major limitations, including data sparsity. Sparse data affect the quality of the user similarity measurement and consequently the quality of the recommender system. In this paper, we propose a novel user similarity measure based...

Now a day E-learning is becoming popular as it helps to fulfil the necessities of remote students and helps the teaching-learning process in Education system. Course Recommender System in E-Learning is a system which recommend the course to the student based on the choice of various student collected from huge amount of data of courses offered through Moodle package of the college. Here in this...

A recommender system is an information selection that offers preferences to users and enhances their decision-making. This commonly implemented in human-computer-interaction (HCI) intervention because of its filtering personalization. However, success rate decision-making considered low the rationale for this associated with users’ psychological reactance which causing unsuccessful intervention...

Abstract Recommender systems are information filtering used in many online applications like music and video broadcasting e-commerce platforms. They also increasingly being applied to facilitate software engineering activities. Following this trend, we witnessing a growing research interest on recommendation approaches that assist with modelling tasks model-based development processes. In paper...

SARA, the Student Advice Recommender Agent is a system somewhat like an early alert system, where predictive models of learners’ success combined with incremental data on learners’ activity in a course can be used to identify students in academic distress. With SARA, rather than give alerts to academic advisors or professors, we provide personalized advice directly to students. An advice string...