
Fractal ETIS thinks this is interesting:
A slightly more sophisticated way to determine the similarity between people’s interests is to use a Pearson correlation coefficient. The correlation coefficient is a measure of how well two sets of data fit on a straight line. The formula for this is more complicated than the Euclidean distance score, but it tends to give better results in situations where the data isn’t well normalized—for example, if critics’ movie rankings are routinely more harsh than average.
From
 2. Making Recommendations
 from Programming Collective Intelligence
 Publisher: O'Reilly Media, Inc.
 Released: August 2007
Note
Collaborative Filtering is used by recommendation engines
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