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Interactively exploring supply and demand in the UK independent music scene

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Abstract
We present an exploratory data mining tool useful for finding patterns in the geographic distribution of independent UK-based music artists. Our system is interactive, highly intuitive, and entirely browser-based, meaning it can be used without any additional software installations from any device. The target audiences are artists, other music professionals, and the general public. Potential uses of our software include highlighting discrepancies in supply and demand of specific music genres in different parts of the country, and identifying at a glance which areas have the highest densities of independent music artists.

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MLA
McVicar, Matthew et al. “Interactively Exploring Supply and Demand in the UK Independent Music Scene.” Lecture Notes in Artificial Intelligence. Vol. 9286. Berlin, Germany: SPRINGER-VERLAG BERLIN, 2015. 289–292. Print.
APA
McVicar, Matthew, Mesnage, C., Lijffijt, J., & De Bie, T. (2015). Interactively exploring supply and demand in the UK independent music scene. Lecture Notes in Artificial Intelligence (Vol. 9286, pp. 289–292). Presented at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Berlin, Germany: SPRINGER-VERLAG BERLIN.
Chicago author-date
McVicar, Matthew, Cedric Mesnage, Jefrey Lijffijt, and Tijl De Bie. 2015. “Interactively Exploring Supply and Demand in the UK Independent Music Scene.” In Lecture Notes in Artificial Intelligence, 9286:289–292. Berlin, Germany: SPRINGER-VERLAG BERLIN.
Chicago author-date (all authors)
McVicar, Matthew, Cedric Mesnage, Jefrey Lijffijt, and Tijl De Bie. 2015. “Interactively Exploring Supply and Demand in the UK Independent Music Scene.” In Lecture Notes in Artificial Intelligence, 9286:289–292. Berlin, Germany: SPRINGER-VERLAG BERLIN.
Vancouver
1.
McVicar M, Mesnage C, Lijffijt J, De Bie T. Interactively exploring supply and demand in the UK independent music scene. Lecture Notes in Artificial Intelligence. Berlin, Germany: SPRINGER-VERLAG BERLIN; 2015. p. 289–92.
IEEE
[1]
M. McVicar, C. Mesnage, J. Lijffijt, and T. De Bie, “Interactively exploring supply and demand in the UK independent music scene,” in Lecture Notes in Artificial Intelligence, Porto, Portugal, 2015, vol. 9286, pp. 289–292.
@inproceedings{7000073,
  abstract     = {{We present an exploratory data mining tool useful for finding patterns in the geographic distribution of independent UK-based music artists. Our system is interactive, highly intuitive, and entirely browser-based, meaning it can be used without any additional software installations from any device. The target audiences are artists, other music professionals, and the general public. Potential uses of our software include highlighting discrepancies in supply and demand of specific music genres in different parts of the country, and identifying at a glance which areas have the highest densities of independent music artists.}},
  author       = {{McVicar, Matthew and Mesnage, Cedric and Lijffijt, Jefrey and De Bie, Tijl}},
  booktitle    = {{Lecture Notes in Artificial Intelligence}},
  isbn         = {{978-3-319-23461-8}},
  issn         = {{0302-9743}},
  language     = {{eng}},
  location     = {{Porto, Portugal}},
  pages        = {{289--292}},
  publisher    = {{SPRINGER-VERLAG BERLIN}},
  title        = {{Interactively exploring supply and demand in the UK independent music scene}},
  url          = {{http://dx.doi.org/10.1007/978-3-319-23461-8_32}},
  volume       = {{9286}},
  year         = {{2015}},
}

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