We present an exploratory data mining tool useful for finding patterns in the geographic distribution of independent UK-based music artists. Our system is interactive, highly intuitive, and entirely browser-based, meaning it can be used without any additional software installations from any device. The target audiences are artists, other music professionals, and the general public. Potential us...

The paper begins with a response to the nature of contemporary artists relationships to how computers have permeated the fine art domain and how they affect the creative process. How should artists utilize this tool in order to fully understand and explore its potential? Using the example of a recent project I have undertaken called 'nGen', I shall discuss some aspects of how the computer tool ...

One of the most useful signals for building a music similarity representation for recommendation comes from learning a collaborative filtering (CF) space from user data such as user listening behavior and user ratings. However, the distribution of this data is heavily biased towards the most popular music, what we call the head of the distribution. We have much less data on less popular artists...

In this paper, differences between multichannel EEG signals of artists and nonartists were analyzed during visual perception and mental imagery of some paintings and at resting condition using approximate entropy (ApEn). It was found that ApEn is significantly higher for artists during the visual perception and the mental imagery in the frontal lobe, suggesting that artists process more informa...