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
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;
Journal_Title :
Multimedia, IEEE Transactions on
DOI :
10.1109/TMM.2014.2325693