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Flytrap: intelligent group music recommendation
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Source International Conference on Intelligent User Interfaces archive
Proceedings of the 7th international conference on Intelligent user interfaces table of contents
San Francisco, California, USA
SESSION: Short Papers table of contents
Pages: 184 - 185  
Year of Publication: 2002
ISBN:1-58113-459-2
Authors
Andrew Crossen  Northwestern University, Evanston, IL
Jay Budzik  Northwestern University, Evanston, IL
Kristian J. Hammond  Northwestern University, Evanston, IL
Sponsors
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 5,   Downloads (12 Months): 39,   Citation Count: 7
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ABSTRACT

Flytrap is a group music environment that knows its users' musical tastes and can automatically construct a soundtrack that tries to please everyone in the room. The system works by paying attention to what music people listen to on their computers. Users of the system have radio frequency ID badges that let the system know when they are nearby. Using the preference information it has gathered from watching its users, and knowledge of how genres of music interrelate, how artists have influenced each other, and what kinds of transitions between songs people tend to make, the 'virtual DJ' finds a compromise and chooses a song. The system tries to satisfy the tastes of people in the room, but it also makes a playlist that fits its own notion of what should come next. Once it has chosen a song, music is automatically broadcast over the network and played on the closest machine.



CITED BY  7

Collaborative Colleagues:
Andrew Crossen: colleagues
Jay Budzik: colleagues
Kristian J. Hammond: colleagues