Data Informed — “The Value in a Facebook Game: Training Machines to Characterize Music Selections”

Dedham, Massachusetts – May 31, 2012

Data Informed announces a new article, “The Value in a Facebook Game: Training Machines to Characterize Music Selections” available in the online publication.

Online PR News – 03-June-2012 – Dedham, Massachusetts – Data Informed announces a new article, “The Value in a Facebook Game: Training Machines to Characterize Music Selections” available in the online publication.

Seeking to build a "Google for music," University of California at San Diego engineers created a Facebook app to provide training data for their machine learning system, using social gamers to characterize songs instead of paying experts like Pandora.

The UCSD Computer Audition Laboratory game powered machine learning system also trained its game, Herd It, to ask players questions about music the machines had trouble recognizing, constantly seeking to improve its own recognition techniques. The result is a system that can already categorize music much faster than the competition, and could result in a "zero-click" radio station that reads your mood and recommends the perfect playlist.

The article is located at: http://data-informed.com/the-value-in-a-facebook-game-training-machines-to-characterize-music-selections/
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Data Informed is the leading resource for business and IT professionals looking for news, in-depth case studies, expert insight, best practices, and product analyses to plan and implement their data analytics and management strategies.
Data Informed gives decision makers perspective on how they can apply big data concepts and technologies to their business needs. With original insight, ideas, and advice, we also explain the potential risks and benefits of introducing new data technology into existing data systems.
About WIS Publishing:
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