November 2, 2006

Use Case: Discovering Indie Bands

Filed under: syminfo — syminfo @ 2:49 pm

LIST: Best Groups To Listen To While Driving
– The Deadlights
– Static-X
– Rage Against The Machine
– 311
– Incubus
20 Reasons Taken (indie band out of Milwaukee)

Some other random person from some little town in CA has a similar driving music list: it contains the same first 5 items in my list, and some 6th band, an indie band from LA.

Our lists are 83% similar to each other.  We can each discover some good driving music that was undiscoverable through traditional marketing channels.

It is possible to measure the value of undiscovered data between any two lists.  I’m still trying to get my head around the math involved with this… and how far people have taken this stuff.  I’ve checked out Set Theory extensively.  I’m trying to not reinvent too many wheels here…

Scalability of the system… As the number of lists grows within the system, the potential value of undiscovered data grows with it.  Reed’s Law observes that the utility of networks scale exponentially with the network’s size.  Given a set of n lists, there are n^2 possible subsets from which to measure undiscovered data.

Scalability of lists… Imagine exporting your iTunes playlists (5-star songs) out to a system with 10,000 users.  Other users see your list and decide to create their own 5-star songs lists.  Others decide they want to create a list of their 1-star songs (the worst in their libraries).  Your 5-star songs will share items from any of these groups, and if the items of the groups are similar enough, you will discover music to add to your own set.  You benefit from similar lists, regardless of their contexts.

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1 Comment »

  1. Great to see we made your list! Thanks for the support!
    ~Mison / 20 Reasons Taken

    P.S. The new disk will be out this summer!

    Comment by Mison — May 31, 2007 @ 7:48 pm


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