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The Science and Technology of Music

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Research Project: Music recommendation engine

Back to Research Field: Music Perception and Cognition

Music recommendation engine

  Research Project Information
Runtime: May 31, 2005 until Apr 30, 2006
Scientific staff: Douglas Eck (U. de Montréal, Informatique et recherche opérationnelle); Daniel Levitin (McGill, Psychology); Yoshua Bengio; Hadiya Nedd-Roderique; Sandy Pearlman
Funding: Bell Canada Enterprises; Natural Sciences and Engineering Research Council of Canada (NSERC)

A new adaptive learning music recommendation system automatically suggests songs to listeners based on knowledge of past preferences, song descriptions, and personal demographic information. A personalized playlist tailored to the listener's preferences is created automatically, and the musical selections are broadcast through the Internet. The listener can provide feedback information about the music presented to him or her in order to improve the automatic selection of music.