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Game-Theoretic Sponsored Search and Human Computation
PhD Thesis Proposal Defence Title: "Game-Theoretic Sponsored Search and Human Computation" by Mr. Georgios TRIMPONIAS Abstract: This thesis applies concepts and tools from game theory in two areas with immense industrial potential, sponsored search and human computation. In sponsored search, we investigate contextualized advertising, where advertisers have different valuations for different disjoint contexts and the number of queries per context is known in advance. When no budget constraints exist, we properly adapt the GSP auction, and explore combinatorial auctions. When budget constraints are present, we distinguish between two cases: advertisers may be indifferent to the price per click, or they may not be willing to pay more than their valuation. For the first case, we utilize a novel probabilistic framework that is inspired by resource allocation markets. Under reasonable conditions, a Nash equilibrium always exists; to compute it, we introduce three methods based on distributed dynamics. In the second case, we cannot show that a Nash equilibrium always exists, but we manage to bound a player??s most profitable deviation using concave relaxations of the utilities. In human computation, we address two fundamental problems in human computation games. The first concerns methods for ranking players according to their skill. We discuss how human computation games are weak-link games, where low-skill players have a disproportionately greater impact on the game outcome. We then develop three ELO-based techniques that consider the weak-link structure as well as the task difficulty. Moreover, we introduce a Bayesian skill rating system, and show how to perform approximate inference using Expectation Propagation and a proportional heuristic for updating the posterior marginals. The second problem regards the mechanism design for generalizations of the ESP game. We apply Bayesian game theory to model and analyze how players behave in equilibrium. Our analysis explains how rational and strategic players may resort to adversarial actions to increase their score. To tackle this, we introduce an improved proportional mechanism. Date: Friday, 14 November 2014 Time: 2:00pm - 4:00pm Venue: Room 3494 lifts 25/26 Committee Members: Prof. Qiang Yang (Supervisor) Prof. Dimitris Papadias (Chairperson) Prof. Dit-Yan Yeung Prof. Yang Wang (MATH) **** ALL are Welcome ****