Model-based feedback in the language modeling approach to information retrieval
Proceedings of the tenth international conference on Information and knowledge management
A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
A large-scale analysis of query logs for assessing personalization opportunities
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Predicting clicks: estimating the click-through rate for new ads
Proceedings of the 16th international conference on World Wide Web
Using query contexts in information retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Contextual advertising by combining relevance with click feedback
Proceedings of the 17th international conference on World Wide Web
Introduction to Information Retrieval
Introduction to Information Retrieval
How much can behavioral targeting help online advertising?
Proceedings of the 18th international conference on World wide web
Large-scale behavioral targeting
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Personalized news recommendation based on click behavior
Proceedings of the 15th international conference on Intelligent user interfaces
Extracting user profiles from large scale data
Proceedings of the 2010 Workshop on Massive Data Analytics on the Cloud
Ranking for the conversion funnel
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Sequential selection of correlated ads by POMDPs
Proceedings of the 21st ACM international conference on Information and knowledge management
Enabling direct interest-aware audience selection
Proceedings of the 21st ACM international conference on Information and knowledge management
Towards a robust modeling of temporal interest change patterns for behavioral targeting
Proceedings of the 22nd international conference on World Wide Web
Permutation indexing: fast approximate retrieval from large corpora
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Web applications often rely on user profiles of observed user actions, such as queries issued, page views, etc. In audience selection for display advertising, the audience that is likely to be responsive to a given ad campaign is identified via such profiles. We formalize the audience selection problem as a ranked retrieval task over an index of known users. We focus on the common case of audience selection where a small seed set of users who have previously responded positively to the campaign is used to identify a broader target audience. The actions of the users in the seed set are aggregated to construct a query, the query is then executed against an index of other user profiles to retrieve the highest scoring profiles. We validate our approach on a real-world dataset, demonstrating the trade-offs of different user and query models and that our approach is particularly robust for small campaigns. The proposed user modeling framework is applicable to many other applications requiring user profiles such as content suggestion and personalization.