Each year that the competition was running NetFlix awarded a progress prize to the best ranked team at the end of the year. Part of the requirements of winning this prize is publication of scientific papers describing key elements of their algorithms. BellKor's Yehuda Koren presented a paper at SIGKIDD in July describing the improvements they made to their algorithm to take advantage of predictable temporal dynamics of ratings. Check out the paper here

From an article about the paper:

While movies themselves stay the same, the humans who rate them are anything but static. As Koren puts it, "The way I rate movies today can be very different from how I rate them even tomorrow." To the frustration of Netflix Prize contenders, a four-star rating can mean "great" or merely "so-so" depending on the user's current mood or comparisons with other recently seen movies. Besides such erratic shifts in the rating scale, people's actual tastes tend to change over time -- as when someone tires of action films, for example, and develops a yen for screwball comedies. There's an overall rise in ratings over the years, as well: for various reasons, a typical movie's ratings become more favorable as the DVD ages.

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