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- W2525740015 abstract "We introduce a new class of algorithms to estimate the cardinality of very large multisets using constant memory and doing only one pass on the data. It is based on order statistics rather that on bit patterns in binary representations of numbers. We analyse three families of estimators. They attain a standard error of $frac{1}{sqrt{M}}$ using $M$ units of storage, which places them in the same class as the best known algorithms so far. They have a very simple internal loop, which gives them an advantage in term of processing speed. The algorithms are validated on internet traffic traces." @default.
- W2525740015 created "2016-10-07" @default.
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- W2525740015 date "2005-01-01" @default.
- W2525740015 modified "2023-09-25" @default.
- W2525740015 title "Order statistics and estimating cardinalities of massive data sets" @default.
- W2525740015 doi "https://doi.org/10.46298/dmtcs.3353" @default.
- W2525740015 hasPublicationYear "2005" @default.
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