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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.
Collaborative Filtering is used by recommendation enginesFrom
Note
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