Recommender systems have become an important research field since the emergence of
the first paper on collaborative filtering in the mid-1990s. Although academic research on …

Recommender system (RS) has emerged as a major research interest that aims to help
users to find items online by providing suggestions that closely match their interest. This …

E-business leverages digital channels to scale its functions and services and operates by
connecting and retaining customers using marketing initiatives. To increase the likelihood of …

A recommender system aims to provide users with personalized online product or service
recommendations to handle the increasing online information overload problem and …

Recommender systems have developed in parallel with the web. They were initially based
on demographic, content-based and collaborative filtering. Currently, these systems are …

Due to the explosion of available information on the Internet, the need for effective means of
accessing and processing them has become vital for everyone. Recommender systems …

The topic of semantic segmentation has witnessed considerable progress due to the
powerful features learned by convolutional neural networks (CNNs). The current leading …

In the past decade large scale recommendation datasets were published and extensively
studied. In this work we describe a detailed analysis of a sparse, large scale dataset …

The music domain is among the most important ones for adopting recommender systems
technology. In contrast to most other recommendation domains, which predominantly rely on …

Originating from Facebook, LinkedIn, Twitter, Instagram, YouTube, and many other
networking sites, the social media shared by users and the associated metadata are …