Recommender systems are software tools and techniques for suggesting items in an
automated fashion to users tailored their preferences. Collaborative Filtering (CF) …

Rapid growth of web and its applications has created a colossal importance for
recommender systems. Being applied in various domains, recommender systems were …

Due to increase in complexity of modelling human behaviour in virtual environment,
traditional or conventional didactic learning is limited in providing flexible or dynamic e …

The association-rule-based approach is one of the most common technologies for building
recommender systems and it has been extensively adopted for commercial use. A variety of …

As higher education diversifies its delivery modes, our ability to use the predictive and
analytical power of educational data mining (EDM) to understand students' learning …

This article argues that there is a need for Personal Recommender Systems (PRSs) in
Learning Networks (LNs) in order to provide learners with advice on the suitable learning …

Fifty years ago there were just a handful of universities across the globe that could provide
for specialized educational courses. Today Universities are generating not only graduates …

Learning management systems (LMS) are typically used by large educational institutions
and focus on supporting instructors in managing and administrating online courses …

In this paper, we present a data-based user modeling framework that uses both
unsupervised and supervised classification to build student models for exploratory learning …

The rapid development of e-learning systems provides learners with great opportunities to
access learning activities online, and this greatly supports and enhances the learning …