Bundling Information Goods: Pricing, Profits, and Efficiency
Management Science
Truthful auctions for pricing search keywords
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Approximating revenue-maximizing combinatorial auctions
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Sponsored search with contexts
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
IEEE Transactions on Communications
Proceedings of the VLDB Endowment
Buy-it-now or take-a-chance: a simple sequential screening mechanism
Proceedings of the 20th international conference on World wide web
Multi-keyword sponsored search
Proceedings of the 12th ACM conference on Electronic commerce
Send mixed signals: earn more, work less
Proceedings of the 13th ACM Conference on Electronic Commerce
Signaling schemes for revenue maximization
Proceedings of the 13th ACM Conference on Electronic Commerce
Revenue maximization via hiding item attributes
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Signaling Competition and Social Welfare
ACM Transactions on Economics and Computation
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A context in sponsored search is additional information about a query, such as the user's age, gender or location, that can change an advertisement's relevance or an advertiser's value for that query. Given a set of contexts, advertiser welfare is maximized if the search engine runs a separate auction for each context; however, due to lack of competition within contexts, this can lead to a significant loss in revenue. In general, neither separate auctions nor pure bundling need maximize revenue. With this motivation, we study the algorithmic question of computing the revenue-maximizing partition of a set of items under a secondprice mechanism and additive valuations for bundles. We show that the problem is strongly NP-hard, and present an algorithm that yields a 1/2- approximation of the revenue from the optimal partition. The algorithm simultaneously yields a 1/2-approximation of the optimal welfare, thus ensuring that the gain in revenue is not at the cost of welfare. Finally we show that our algorithm can be applied to the sponsored search setting with multiple slots, to obtain a constant factor approximation of the revenue from the optimal partition.