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We present a simple, intuitive algorithm for the problem of finding an approximate list of the k most frequent items in a data stream when the item frequencies are Zipf-distributed. Our result improves the previous result of Charikar, Chen and Farach-Colton for the same problem when the Zipf parameter is low. We also highlight an application of the algorithm to web caching that may be of practical interest.

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