Computational geometry: an introduction
Computational geometry: an introduction
A threshold of ln n for approximating set cover (preliminary version)
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Greedy facility location algorithms analyzed using dual fitting with factor-revealing LP
Journal of the ACM (JACM)
AdWords and Generalized On-line Matching
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
Truthful auctions for pricing search keywords
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
An adaptive algorithm for selecting profitable keywords for search-based advertising services
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Dynamics of bid optimization in online advertisement auctions
Proceedings of the 16th international conference on World Wide Web
Bidding to the top: VCG and equilibria of position-based auctions
WAOA'06 Proceedings of the 4th international conference on Approximation and Online Algorithms
Online budgeted matching in random input models with applications to Adwords
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
A Knapsack Secretary Problem with Applications
APPROX '07/RANDOM '07 Proceedings of the 10th International Workshop on Approximation and the 11th International Workshop on Randomization, and Combinatorial Optimization. Algorithms and Techniques
Bid optimization for broad match ad auctions
Proceedings of the 18th international conference on World wide web
The adwords problem: online keyword matching with budgeted bidders under random permutations
Proceedings of the 10th ACM conference on Electronic commerce
Expressive banner ad auctions and model-based online optimization for clearing
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Mining advertiser-specific user behavior using adfactors
Proceedings of the 19th international conference on World wide web
Conversion rate based bid adjustment for sponsored search
Proceedings of the 19th international conference on World wide web
Stochastic models for budget optimization in search-based advertising
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
ACM Transactions on Internet Technology (TOIT)
Keyword auction protocol for dynamically adjusting the number of advertisements
Web Intelligence and Agent Systems
Optimizing budget allocation among channels and influencers
Proceedings of the 21st international conference on World Wide Web
Joint optimization of bid and budget allocation in sponsored search
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Sponsored search auctions: an overview of research with emphasis on game theoretic aspects
Electronic Commerce Research
Maximizing revenue from strategic recommendations under decaying trust
Proceedings of the 21st ACM international conference on Information and knowledge management
Optimizing budget constrained spend in search advertising
Proceedings of the sixth ACM international conference on Web search and data mining
Budget optimization for online campaigns with positive carryover effects
WINE'12 Proceedings of the 8th international conference on Internet and Network Economics
Budget smoothing for internet ad auctions: a game theoretic approach
Proceedings of the fourteenth ACM conference on Electronic commerce
Dynamic dual adjustment of daily budgets and bids in sponsored search auctions
Decision Support Systems
Electronic Commerce Research and Applications
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Internet search companies sell advertisement slots based on users' search queries via an auction. While there has been previous work onthe auction process and its game-theoretic aspects, most of it focuses on the Internet company. In this work, we focus on the advertisers, who must solve a complex optimization problem to decide how to place bids on keywords to maximize their return (the number of user clicks on their ads) for a given budget. We model the entire process and study this budget optimization problem. While most variants are NP-hard, we show, perhaps surprisingly, that simply randomizing between two uniform strategies that bid equally on all the keywordsworks well. More precisely, this strategy gets at least a 1-1/ε fraction of the maximum clicks possible. As our preliminary experiments show, such uniform strategies are likely to be practical. We also present inapproximability results, and optimal algorithms for variants of the budget optimization problem.