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U ABSTRACT This paper considers the problem of scalably processing a large number of continuous queries. We propose a flexible framework with novel data structures and algorithms for group-processing and indexing continuous queries by exploiting potential overlaps in query predicates. Our approach partitions the collection of continuous queries into groups based on the clustering patterns of the query ranges, and then applies specialized processing strategies to those heavily-clustered groups (o.
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