Here is a recent Google correlate query:
As you can see in the search box at that link, I entered "internet usage" and Google did the rest. It shows a value of 0.9298 as the "correlation" with the query "data mining". However, when I read page 2 of the Google white paper [PDF], it says:
The objective of Google Correlate is to surface the queries in the database whose spatial or temporal pattern is most highly correlated with a target pattern. Google Correlate employs a novel approximate nearest neighbor (ANN) algorithm over millions of candidate queries in an online search tree to produce results similar to the batch-based approach employed by Google Flu Trends but in a fraction of a second. For additional details, please see the Methods section below....
So, my question is:
Is Google using a normal Pearson or Spearman correlation to find this stuff or are they using something else? If so, can you explain the general technique?
Also, notice in the plot that the search for "internet usage" (and "data mining") drops during the summer months and really dives around Christmas. I would guess that kids and their homework have something to do with this.