acm-header
Sign In

Communications of the ACM

ACM News

How Computers Know What We Want


Recommendation engine

C.J. Burton for TIME

Here's an experiment: try thinking of a song not as a song but as a collection of distinct musical attributes. Maybe the song has political lyrics. That would be an attribute. Maybe it has a police siren in it, or a prominent banjo part, or paired vocal harmony, or punk roots. Any one of those would be an attribute. A song can have as many as 400 attributes--those are just a few of the ones filed under p.

This curious idea originated with Tim Westergren, one of the founders of an Internet radio service based in Oakland, Calif., called Pandora. Every time a new song comes out, someone on Pandora's staff--a specially trained musician or musicologist--goes through a list of possible attributes and assigns the song a numerical rating for each one. Analyzing a song takes about 20 minutes.

The people at Pandora--no relation to the alien planet--analyze 10,000 songs a month. They've been doing it for 10 years now, and so far they've amassed a database containing detailed profiles of 740,000 different songs. Westergren calls this database the Music Genome Project.

There is a point to all this, apart from settling bar bets about which song has the most prominent banjo part ever. The purpose of the Music Genome Project is to make predictions about what kind of music you're going to like next. Pandora uses the Music Genome Project to power what's known in the business as a recommendation engine...

From Time
View Full Article


 

No entries found

Sign In for Full Access
» Forgot Password? » Create an ACM Web Account