Impedance coupling in content-targeted advertising
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
A semantic approach to contextual advertising
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A noisy-channel approach to contextual advertising
Proceedings of the 1st international workshop on Data mining and audience intelligence for advertising
Contextual advertising by combining relevance with click feedback
Proceedings of the 17th international conference on World Wide Web
First workshop on targeting and ranking for online advertising
Proceedings of the 17th international conference on World Wide Web
What happens after an ad click?: quantifying the impact of landing pages in web advertising
Proceedings of the 18th ACM conference on Information and knowledge management
A stochastic learning-to-rank algorithm and its application to contextual advertising
Proceedings of the 20th international conference on World wide web
Retrieval models for audience selection in display advertising
Proceedings of the 20th ACM international conference on Information and knowledge management
Learning to target: what works for behavioral targeting
Proceedings of the 20th ACM international conference on Information and knowledge management
Post-click conversion modeling and analysis for non-guaranteed delivery display advertising
Proceedings of the fifth ACM international conference on Web search and data mining
Finding the right consumer: optimizing for conversion in display advertising campaigns
Proceedings of the fifth ACM international conference on Web search and data mining
Web-scale user modeling for targeting
Proceedings of the 21st international conference companion on World Wide Web
Factoring past exposure in display advertising targeting
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 2013 international conference on Intelligent user interfaces
Towards a robust modeling of temporal interest change patterns for behavioral targeting
Proceedings of the 22nd international conference on World Wide Web
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In contextual advertising advertisers show ads to users so that they will click on them and eventually purchase a product. Optimizing this action sequence, called the conversion funnel, is the ultimate goal of advertising. Advertisers, however, often have very different sub-goals for their ads such as purchase, request for a quote, or simply a site visit. Often an improvement for one advertiser's goal comes at the expense of others. A single ranking function must balance these different goals in order to make an efficient system for all advertisers. We propose a ranking method that globally balances the goals of all advertisers, while simultaneously improving overall performance. Our method has been shown to improve significantly over the baseline in online traffic at a major ad network.