scholarly journals Deep Learning in Music Recommendation Systems

Author(s):  
Markus Schedl
Author(s):  
Zehra Cataltepe ◽  
Berna Altinel

As the amount, availability, and use of online music increase, music recommendation becomes an important field of research. Collaborative, content-based and case-based recommendation systems and their hybrids have been used for music recommendation. There are already a number of online music recommendation systems. Although specific user information, such as, demographic data, education, and origin have been shown to affect music preferences, they are usually not collected by the online music recommendation systems, because users would not like to disclose their personal data. Therefore, user models mostly contain information about which music pieces a user liked and which ones s/he did not and when.


Author(s):  
Catherine Marinagi ◽  
Paris Ntsounos ◽  
John Darryl Pelingo ◽  
Christos Skourlas ◽  
Anastasios Tsolakidis

2017 ◽  
Vol 35 (2) ◽  
pp. 3-24 ◽  
Author(s):  
Nedim Karakayali ◽  
Burc Kostem ◽  
Idil Galip

The article brings to light the use of recommender systems as technologies of the self, complementing the observations in current literature regarding their employment as technologies of ‘soft’ power. User practices on the music recommendation website last.fm reveal that many users do not only utilize the website to receive guidance about music products but also to examine and transform an aspect of their self, i.e. their ‘music taste’. The capacity of assisting users in self-cultivation practices, however, is not unique to last.fm but stems from certain properties shared by all recommendation systems. Furthermore, unlike other oft-studied digital/web technologies of the self which facilitate ‘self-publishing’ vis-à-vis virtual companions in social media, recommender algorithms themselves can act as ‘intimate experts’, accompanying users in their self-care practices. Thus, recommendation systems can facilitate both algorithmic control and creative self-transformation, which calls for a theorization of this new cultural medium as a space of tension.


2020 ◽  
Vol 1 (4) ◽  
Author(s):  
Tran Khanh Dang ◽  
Quang Phu Nguyen ◽  
Van Sinh Nguyen

ICT Express ◽  
2019 ◽  
Vol 5 (2) ◽  
pp. 84-88 ◽  
Author(s):  
Hyeungill Lee ◽  
Jungwoo Lee

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