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Search evaluation was born in the late 50’s and the early 60’s in the U.K. In the beginning it was very basic because back then, search was Boolean. The first evaluation measure was recall. You take a query and 100 documents relevant to it. How many of those documents does your search on that query retrieve? We quickly found out that it was very easy to get 100 percent recall. But we also found that our searches often returned a lot of irrelevant documents along with the relevant ones. So we came up with a second measure: Precision. That tells us what percentage of our search returns is actually good. So if a search returns 100 out of 100 relevant documents for a query, but it returns 1,000 documents total, its recall is 100 percent, but its precision is only 10 percent.
I thought this was cool that they are still today improving the algorithm used to get search results. Not just calling it a day and saying were on top that's it.

Have you tried out the "personalized" results yet? It basically creates a personality type for things you search for. I have not used it enough to get a feel for if its really working or not tho.