| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6864660 | Neurocomputing | 2018 | 32 Pages |
Abstract
Beyond the feature engineering step, both methods exploit the inherent efficiency of extreme learning machines (ELMs) so as to translate, in a personalized fashion, the derived patterns into a listener's score. NeuroPicks method may find applications as an integral part of contemporary music recommendation systems, while NeuroPicksVQ can control the selection of music tracks. Encouraging experimental results, from a pragmatic use of the systems, are presented.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
F.P. Kalaganis, D.A. Adamos, N.A. Laskaris,