Sponsored Search Auctions with Markovian Users
Gagan Aggarwal, Jon Feldman, S. Muthukrishnan, Martin Pal

TL;DR
This paper introduces a Markovian user model for sponsored search auctions, providing a new algorithm for optimal ad assignment that differs from GSP, and proposes a truthful auction mechanism with desirable properties.
Contribution
It presents a novel Markovian user model and an algorithm for optimal ad assignment, along with a truthful auction mechanism based on VCG, improving upon traditional GSP assumptions.
Findings
Optimal assignment differs from GSP under the new model
The proposed auction is truthful and has desirable properties
Algorithm efficiently computes the best ad placement
Abstract
Sponsored search involves running an auction among advertisers who bid in order to have their ad shown next to search results for specific keywords. Currently, the most popular auction for sponsored search is the "Generalized Second Price" (GSP) auction in which advertisers are assigned to slots in the decreasing order of their "score," which is defined as the product of their bid and click-through rate. In the past few years, there has been significant research on the game-theoretic issues that arise in an advertiser's interaction with the mechanism as well as possible redesigns of the mechanism, but this ranking order has remained standard. From a search engine's perspective, the fundamental question is: what is the best assignment of advertisers to slots? Here "best" could mean "maximizing user satisfaction," "most efficient," "revenue-maximizing," "simplest to interact with," or a…
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Taxonomy
TopicsAuction Theory and Applications · Consumer Market Behavior and Pricing · Game Theory and Applications
