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 AdWordsTM. We developed techniques for implementing Best Bets systems addressing performance issues for large scale deployment as efficient query search, incremental updates and dynamic ranking. Categories and Subject Descriptors H.3.3 [Information Systems]: Information Search and Retrieval ? information filtering, retrieval models, search process. General Terms Algorithms, Performance, Experimentation, Theory. Keywords Information retrieval, information filtering, proactive content delivery, query, search.