Department of Computer Science,
Duke University.
Office: LSRC D211.
Email: syu at cs.duke.edu


We study how to process a large number of users over a wide-area network whose interests are characterized by range top-k continuous queries. We prove that for each object update, it is possible to describe the set of affected queries succinctly with messages that can be efficiently disseminated using content-driven networks. We give fast algorithms to reformulate each update into a set of messages whose number is provably optimal, with or without knowing all user interests. We also present extensions to our solution, including an approximate algorithm that trades off between the cost of server-side reformulation and that of user-side post-processing, as well as efficient techniques for batch updates.