Comments on: Netflix Prize

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By: brendano

brendano — Wed, 03 Dec 2008 09:27:01 +0000

Panos — I’ve been thinking about this more but it seems tricky to think of *any* data source that should give new and useful information that’s not already present in the ratings dataset. If two movies have a particular type of interesting connection, and it matters for user preferences, then we should expect already to see it in the user ratings data, as either an SVD-derived factor or in kNN similarity comparisons.

Of course, lots of the errors happen where there’s not a lot of previous data points. Tags, IMDB data, or other metadata might help in those cases…

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Calculating running variance in Python and C++ - Brendan O'Connor's Blog — Fri, 28 Nov 2008 23:51:17 +0000

[...] Netflix Prize [...]

By: Panos Ipeirotis

Panos Ipeirotis — Sun, 23 Nov 2008 00:47:24 +0000

Hmmm….. “Hastings is even considering hiring cinephiles to watch all 100,000 movies in the Netflix library and write up, by hand, pages of adjectives describing each movie, a cloud of tags that would offer a subjective view of what makes films similar or dissimilar.”

Are you thinking what I am thinking? :-)

Wondering if anyone leveraged Turking for the Netflix challenge…