IEEE SI-MDM 2013 : IEEE Transactions on Multimedia Special Issue on Music Data Mining
Call For Papers
Call For Papers --- IEEE Transactions on Multimedia
Special Issue on Music Data Mining
Music Data Mining
During the last few years there has been a dramatic shift in how music is produced, distributed and consumed. A combination of advances in digital storage, audio compression as well as significant increases in network bandwidth has made digital music distribution a reality. Portable music players, computers and smart phones frequently contain personal collections of thousands of music tracks. Digital stores in which users can purchase music contain millions of tracks that can be easily downloaded.
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.
Recent advancements in music listening technologies, in particular, the Internet-based music communities, radio stations and music stores, have introduced several new interesting aspects to the area, such as multimodal analysis of music data, community-based labeling of music, user-generated music tags, and listening pattern analysis. The introduction has made the area an exciting research ground and there is a strong and emergent need to publicize the area in multimedia literature.
The topics covered are (but not limited to):
· Keyword generation from song lyrics
· Multi-modal classification and clustering of songs
· Knowledge mining from symbolic (such as MIDI) data
· Knowledge discovery from biography and discography
· Modeling of music listening patterns
· Playlist generation
· Similarity queries
· Classification of genre/style/mood
· Music recommendation
· Music summarization
· Text/web mining for music analysis
· Database systems/indexing/query models for music analysis
· Metadata collection/analysis
Submissions should be submitted through the IEEE Trans. on Multimedia journal web server (http://mc.manuscriptcentral.com/tmm-ieee). Papers should be formatted according to the guidelines for authors (http://www.signalprocessingsociety.org/tmm/tmm-author-info/). During the submission, the authors should indicate that this is a submission for the special issue on “Music Data Mining” (i.e., select the appropriate special issue title under the category “Manuscript Type”). All submissions will undergo a blind peer review by three expert reviewers to ensure a high standard of quality. Referees will consider originality, significance, technical soundness, clarity of exposition, and relevance to the special issue topics above.
· Paper submission due: November 19, 2012
· First-round acceptance notification: March 19, 2013
· Revision Due: June 19, 2013
· Second-round review completed: August 19, 2013
· Final manuscript due: October 19, 2013
· Tentative Publication date: August 2014
· Tao Li, School of Computer Science, Florida International University, USA, email: firstname.lastname@example.org (Lead Guest Editor)
· Mitsunori Ogihara, Department of Computer Science, University of Miami, USA.
· George Tzanetakis, Department of Computer Science, University of Victoria, Canada.
Please address all correspondences regarding this special issue to the Guest Editors.