Information filtering and information retrieval: two sides of the same coin?
Communications of the ACM - Special issue on information filtering
Index structures for selective dissemination of information under the Boolean model
ACM Transactions on Database Systems (TODS)
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
To swing or not to swing: learning when (not) to advertise
Proceedings of the 17th ACM conference on Information and knowledge management
Contextual advertising using keyword extraction through collocation
Proceedings of the 7th International Conference on Frontiers of Information Technology
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Proceedings of the 18th Brazilian symposium on Multimedia and the web
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A number of applications require selecting targets for specific contents on the basis of criteria defined by the contents providers rather than selecting documents in response to user queries, as in ordinary information retrieval. We present a class of retrieval systems, called Best Bets, that generalize Information Filtering and encompass a variety of applications including editorial suggestions, promotional campaigns and targeted advertising, such as Google AdWords™. We developed techniques for implementing Best Bets systems addressing performance issues for large scale deployment as efficient query search, incremental updates and dynamic ranking.