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Archive for the ‘Algorithms’ Category
New Tastes and Genres
In: Algorithms| Movies| New Features| Research
27 May 2009Dr. Dolittle is probably not the first movie that comes to mind when you think of an action-packed movie. But to some people (i.e. our moms who once fed and may still feed us), Dr. Dolittle certainly could be considered an action-packed comedy.
Understanding how most people interpret films is one of the hardest challenges for [...]
Don’t use python’s list comprehensions for set operations. Use, um, the set type and her functions.
In: Algorithms| Code
9 Sep 2008I’m making, say, 60,000 function calls, each involving two python lists (no duplicates within these lists, so they’re theoretically more like sets), with each having some overlap with the other. I’m making these 60,000 calls, say, 30,000 times. The question: how do I find the symmetric difference of the two lists efficiently via my function [...]
Value of recommendation engines
In: Algorithms| Market
31 Jul 2008MIT technology review, which apparently has been published since 1899 according to the cover, in May 2008 published an article by Michael Schrage, “Recommendation Nation”. The last few paragraphs:
For all my excitement about the future of recommendation services, I can’t help feeling the way I felt about search in 2001. Existing recommendation engines have a [...]
What the impending The Dark Knight / Godfather War tells us about the IMDb Top 250
In: Algorithms| Market
29 Jul 2008Movie lovers are a pretty intense bunch. And we should know – we’re rather insane movie lovers ourselves. But it seems that two classes of film lovers are poised for an all-out war. A recent /film blog post reports that The Dark Knight has overtaken The Godfather on the IMDb Top 250 list:
The Godfather has [...]
How we will beat Netflix
In: Algorithms
8 Apr 2008The Netflix Challenge is a $1 million prize for an improved movie recommendation algorithm that does better than the Netflix algorithm at predicting how a user will rate a movie.
Different teams, including some at Stanford, have adopted various approaches to the problem including very, very sophisticated algorithms. But a few teams have taken a different [...]
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