Abstract. Microsoft adCenter is the third largest Search advertising platform in the United States behind Google and Yahoo, and services about 10% of US traffic. At this scale of traffic approximately 1 billion events per hour, amount-ing to $2.3 billion ad dollars annually, need to be scored to determine if it is fraudulent or bot-generated [46], [51], [58]. In order to accomplish this, adCenter has developed arguably one of the largest data mining systems in the world to score traffic quality, and has employed them successfully over five years. The current paper describes the unique challenges posed by data mining at massive scale, the design choices and rationale behind the technologies to address the problem, and shows some examples and some quantitative results on the effectiveness of the system in combating click fraud.
