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11

VLDB
2002
ACM

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Approximate Frequency Counts over Data Streams

13 years 4 months ago

Approximate Frequency Counts over Data Streams

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We present algorithms for computing frequency counts exceeding a user-specified threshold over data streams. Our algorithms are simple and have provably small memory footprints. Although the output is approximate, the error is guaranteed not to exceed a user-specified parameter. Our algorithms can easily be deployed for streams of singleton items like those found in IP network monitoring. We can also handle streams of variable sized sets of items exemplified by a sequence of market basket transactions at a retail store. For such streams, we describe an optimized implementation to compute frequent itemsets in a single pass.

Gurmeet Singh Manku, Rajeev Motwani

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Algorithms | Database | Small Memory Footprints | User-specified Threshold | VLDB 2002 |

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Added	23 Dec 2010
Updated	23 Dec 2010
Type	Journal
Year	2002
Where	VLDB
Authors	Gurmeet Singh Manku, Rajeev Motwani

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