Peer-assisted content delivery networks have recently emerged as an economically viable
alternative to traditional content delivery approaches: the feasibility studies conducted for …

A growing interest in synthetic data has stimulated the development and advancement of a
large variety of deep generative models for a wide range of applications. However, as this …

This article presents an exploratory study of the network of associations among 22,141
YouTube music videos retrieved by 'following'the platform's recommender algorithm, which …

This research aims to analyze the effect of feature selection on the accuracy of music
popularity classification using machine learning algorithms. The data of Spotify, the most …

The corporate rhetoric of streaming platforms often assumes a tight link between their scale-
making ambitions on the one hand and the creative interests of musicians on the other. In …

With the popularity of online music services, personalized music recommendation has
garnered much research interest. Recommendation models are typically trained on datasets …

In streaming media applications, like music Apps, songs are recommended in a continuous
way in users' daily life. The recommended songs are played automatically although users …

Abstract Network Function Virtualization (NFV) decouples network function (also called
middlebox function) software from specified appliances onto general shared servers. Thus, it …

There is an unprecedented opportunity for psychologists and behavioral scientists to merge
prior theory and research with big data to develop profound insights into the way people use …

The evolving digital economy entails multifaceted behavioral tracking data such as internet
clickstreams, location trajectories, or taste preferences revealed by music or video …