As an AdSense Product Manager for ads quality, I'm part of a group that works to make the ads on your site relevant for users. One of the ways we do this is through contextual targeting, which matches ads to the content of your webpages. With contextual targeting, our system parses and analyzes the content of your page, conducts an auction among the relevant ads, then serves the winning ads -- all in the blink of an eye! Pretty simple, right?
Actually, matching relevant ads to the content of your pages is quite a scientific challenge involving semantic analysis and machine learning. It's a challenge that keeps me and my team busy. Our machines are very good at the matching process, but there are still a few cases where their definition of relevance differs from our human definition of relevance. In these few cases, the system might end up serving ads that don't seem immediately relevant to users. We understand that increased ad relevance contributes to a positive experience for users, publishers, and advertisers, so we're continuously working on ways to improve the relevance and quality of ads that appear on your sites.
AdSense and the science of contextual matching
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