Recommender systems are a key technology for many applications, such as e-commerce,
streaming media, and social media. Traditional recommender systems rely on collaborative …

Nowadays, the increasing demand for group recommendations can be observed. In this
paper we address the problem of recommendation performance for groups of users (group …

The act of reading has benefits for individuals and societies, yet studies show that reading
declines, especially among the young. Recommender systems can help stop such decline …

Objective The centrality of data to biomedical research is difficult to understate, and the
same is true for the importance of the biomedical literature in disseminating empirical …

In traditional learning, learners and their lecturers, or tutors can meet face-to-face. In such
lectures, the lecturers, or tutors can introduce printed book tutorials. However, in several …

E-reading has become more popular by making the number of book readers high in number.
With online book reading websites, it is much simpler to read any book at any time by simply …

This paper introduces a new framework for the organization of electronic books (e-books)
and their corresponding authors using a multilayer self-organizing map (MLSOM). An author …

A Recommender System (RS) is an intelligent system that assists users in finding the items
of their interest (eg books, movies, music) by preventing them to go through huge piles of …

Promoting good reading habits among children is essential, given the enormous influence of
reading on students' development as learners and members of the society. Unfortunately …

The data sparsity problem has attracted significant attention in collaborative filtering-based
recommender systems. To alleviate data sparsity, several previous efforts employed hybrid …