DocumentCode
1760620
Title
Guest Editorial: Special Section on Music Data Mining
Author
Li, Tong ; Ogihara, Mitsunori ; Tzanetakis, G.
Author_Institution
School of Computer Science, Florida International University, Miami, FL, USA
Volume
16
Issue
5
fYear
2014
fDate
Aug. 2014
Firstpage
1185
Lastpage
1187
Abstract
The five articles in this special section focus on data mining techniques and applications in the music industry. Music has been an important application area for data mining and machine learning techniques for many years. Music data mining is an interdisciplinary area that studies computational methods for understanding and delivering music data and is a topic of growing importance with large commercial relevance and substantial potential. The research area of music data mining has gradually evolved during this time period in order to address the challenge of effectively accessing and interacting with these increasing large collections of music and associated data such as styles, artists, lyrics and music reviews. The algorithms and systems developed frequently employ sophisticated and advanced data mining and machine learning techniques in their attempt to better capture the frequently elusive relevant music information.
Keywords
Computational modeling; Data mining; Expert systems; Information filtering; Machine learning; Music; Performance evaluation; Recommender systems; Special issues and sections; Unsupervised learning;
fLanguage
English
Journal_Title
Multimedia, IEEE Transactions on
Publisher
ieee
ISSN
1520-9210
Type
jour
DOI
10.1109/TMM.2014.2325693
Filename
6856270
Link To Document