An optimal algorithm for on-line bipartite matching
STOC '90 Proceedings of the twenty-second annual ACM symposium on Theory of computing
Information and Computation
Online computation and competitive analysis
Online computation and competitive analysis
An optimal deterministic algorithm for online b-matching
Theoretical Computer Science
A new greedy approach for facility location problems
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Greedy facility location algorithms analyzed using dual fitting with factor-revealing LP
Journal of the ACM (JACM)
Multi-unit auctions with budget-constrained bidders
Proceedings of the 6th ACM conference on Electronic commerce
AdWords and Generalized On-line Matching
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
Revenue maximization when bidders have budgets
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Truthful auctions for pricing search keywords
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Multi-unit auctions with unknown supply
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
Online primal-dual algorithms for covering and packing problems
ESA'05 Proceedings of the 13th annual European conference on Algorithms
Optimal delivery of sponsored search advertisements subject to budget constraints
Proceedings of the 8th ACM conference on Electronic commerce
AdWords and generalized online matching
Journal of the ACM (JACM)
Online budgeted matching in random input models with applications to Adwords
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
On-line bipartite matching made simple
ACM SIGACT News
A combinatorial allocation mechanism with penalties for banner advertising
Proceedings of the 17th international conference on World Wide Web
Arbitrage opportunities across sponsored search markets
Theoretical Computer Science
A Truthful Mechanism for Offline Ad Slot Scheduling
SAGT '08 Proceedings of the 1st International Symposium on Algorithmic Game Theory
A Cascade Model for Externalities in Sponsored Search
WINE '08 Proceedings of the 4th International Workshop on Internet and Network Economics
Personalized Delivery of On---Line Search Advertisement Based on User Interests
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
Computational analysis of perfect-information position auctions
Proceedings of the 10th ACM conference on Electronic commerce
The adwords problem: online keyword matching with budgeted bidders under random permutations
Proceedings of the 10th ACM conference on Electronic commerce
Optimal Auctions Capturing Constraints in Sponsored Search
AAIM '09 Proceedings of the 5th International Conference on Algorithmic Aspects in Information and Management
Stochastic models for budget optimization in search-based advertising
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
Capacity constraints and the inevitability of mediators in adword auctions
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
Strategy and mechanism lessons from the first ad auctions trading agent competition
Proceedings of the 11th ACM conference on Electronic commerce
Online scheduling of targeted advertisements for IPTV
INFOCOM'10 Proceedings of the 29th conference on Information communications
When LP is the cure for your matching woes: improved bounds for stochastic matchings
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part II
Online stochastic packing applied to display ad allocation
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part I
Keyword auction protocol for dynamically adjusting the number of advertisements
Web Intelligence and Agent Systems
Coverage patterns for efficient banner advertisement placement
Proceedings of the 20th international conference companion on World wide web
Online bipartite matching with unknown distributions
Proceedings of the forty-third annual ACM symposium on Theory of computing
Online bipartite matching with random arrivals: an approach based on strongly factor-revealing LPs
Proceedings of the forty-third annual ACM symposium on Theory of computing
Design of online auctions: Proxy versus non-proxy settings
Decision Support Systems
Simultaneous approximations for adversarial and stochastic online budgeted allocation
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Advertisement allocation for generalized second-pricing schemes
Operations Research Letters
Online scheduling of targeted advertisements for IPTV
IEEE/ACM Transactions on Networking (TON)
Optimizing budget constrained spend in search advertising
Proceedings of the sixth ACM international conference on Web search and data mining
Optimal mediated auctions with endogenous participation
Decision Support Systems
Proceedings of the 23rd international conference on World wide web
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We study the problem of optimally allocating online advertisement space to budget-constrained advertisers. This problem was defined and studied from the perspective of worst-case online competitive analysis by Mehta et al. Our objective is to find an algorithm that takes advantage of the given estimates of the frequencies of keywords to compute a near optimal solution when the estimates are accurate, while at the same time maintaining a good worst-case competitive ratio in case the estimates are totally incorrect. This is motivated by real-world situations where search engines have stochastic information that provide reasonably accurate estimates of the frequency of search queries except in certain highly unpredictable yet economically valuable spikes in the search pattern. Our approach is a black-box approach: we assume we have access to an oracle that uses the given estimates to recommend an advertiser everytime a query arrives. We use this oracle to design an algorithm that provides two performance guarantees: the performance guarantee in the case that the oracle gives an accurate estimate, and its worst-case performance guarantee. Our algorithm can be fine tuned by adjusting a parameter α, giving a tradeoff curve between the two performance measures with the best competitive ratio for the worst-case scenario at one end of the curve and the optimal solution for the scenario where estimates are accurate at the other en. Finally, we demonstrate the applicability of our framework by applying it to two classical online problems, namely the lost cow and the ski rental problems.