The user-based collaborative filtering (UCF) model has been widely used in industry for
recommender systems. UCF predicts a user's interest in an item based on rating information …

Sistemas de Recomendação baseados em Conteúdo (SRbC) é uma área em que
estratégias de Aprendizado de Máquina (AM) podem ser potencialmente aplicadas com …

To enable a quick and accurate access of targeted scientific and technological literature
from massive stocks, here a deep content-based collaborative filtering method, namely …

A recommender system or a recommendation system is a subclass of information filtering
system which in turn predicts the “preference” or “ratings” which a user would provide to the …

Current automatic chord estimation systems are trained and tested using datasets that
contain single reference annotations, ie, for each corresponding musical segment (eg, audio …

With the tremendous amount of research publications online, finding relevant ones for a
particular research topic can be an overwhelming task. As a solution, papers recommender …

Scholarly paper recommendation has been an important research topic in the field of
information filtering because scholars find thousands of publications that match their search …

With the rapid growth of the scholarly literature, finding relevant and influential articles is
becoming increasingly important. Research shows that a scholar's past works represent his …

Abstract Content-based Recommendation Systems (CbRS) is a research area in which
Machine Learning (ML) strategies can be applied with success. However, specifically in …

Model-based approaches for Content-based Filtering (CBF) recommendation have the
potential of generating representative users models owing to their ability to learn from users …