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Abstract: Emerging data stream management systems approach the challenge of massive data distributions which arrive at high speeds while there is only small storage by summarizing and mining the distributions using samples or sketches. However, data distributions can be "viewed" in different ways. A data stream of integer values can be viewed either as the forward distribution f(x), ie., the number of occurrences of x in the stream, or as its inverse, f -1 (i), which is the number of items that ... (Update)
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BibTeX entry: (Update)
@misc{ cormode-summarizing,
author = "Graham Cormode and S. Muthukrishnan and Irina Rozenbaum",
title = "Summarizing and Mining Inverse Distributions on Data Streams via Dynamic
Inverse Sampling",
url = "citeseer.ist.psu.edu/cormode05summarizing.html" }
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