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Finding Top-k Most Frequent Items in Distributed Streams in the Time-Sliding Window Model
Abstract : We propose a new probabilistic algorithm to find the top-k most recent and frequent items in distributed streams. This algorithm significantly improves upon the reliability and accuracy of existing results, while significantly reducing the memory footprint needed by each of the distributed nodes to solve this problem.
Cited literature [6 references]
https://hal-imt-atlantique.archives-ouvertes.fr/hal-01839930
Contributor : Yann Busnel Connect in order to contact the contributor
Submitted on : Monday, July 16, 2018 - 10:59:51 AM
Last modification on : Monday, April 4, 2022 - 9:28:22 AM
Long-term archiving on: : Wednesday, October 17, 2018 - 1:42:13 PM
Contributor : Yann Busnel Connect in order to contact the contributor
Submitted on : Monday, July 16, 2018 - 10:59:51 AM
Last modification on : Monday, April 4, 2022 - 9:28:22 AM
Long-term archiving on: : Wednesday, October 17, 2018 - 1:42:13 PM
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finding-top-k.pdf
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