Today I will introduce Chapter 10: Maximizing Ad-Auctions Revenue in the book of The Design of Competitive Online Algorithms via a Primal-Dual Approach.
Maximizing the revenue of a seller in an online auction has recently received much attention and studied in many models and settings.
In particular, the way search engine companies such as Microsoft, Google, and Yahoo! maximize their revenue out of selling ad-auctions has been studied extensively. In the search engine environment, advertisers link their ads to (search) keywords and provide a bid on the amount paid each time a user clicks on their ad. When users send queries to search engines, along with the (algorithmic) search results returned for each query, the search engine displays funded ads corresponding to ad-auctions. The ads are instantly sold, or allocated, to interested advertisers (buyers). The total revenue out of this fast growing market is currently billions of dollars. Thus, algorithmic ideas that can improve the allocation of ads, even by a small percentage, are crucial.
The slide is also attached.