Static Load Balancing of Parallel Mining of Frequent Itemsets Using Reservoir Sampling

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F11%3A00368102" target="_blank" >RIV/67985807:_____/11:00368102 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-23199-5_41" target="_blank" >http://dx.doi.org/10.1007/978-3-642-23199-5_41</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-23199-5_41" target="_blank" >10.1007/978-3-642-23199-5_41</a>

Result language
angličtina
Original language name
Static Load Balancing of Parallel Mining of Frequent Itemsets Using Reservoir Sampling
Original language description
In this paper, we present a novel method for parallelization of an arbitrary depth-first search (DFS in short) algorithm for mining of all FIs. The method is based on the so called reservoir sampling algorithm. The reservoir sampling algorithm in combination with an arbitrary DFS mining algorithm executed on a database sample takes an uniformly but not independently distributed sample of all FIs using the reservoir sampling. The sample is then used for static load-balancing of the computational load ofa DFS algorithm for mining of all FIs.
Czech name
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Czech description
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Project
<a href="/en/project/GAP202%2F10%2F1333" target="_blank" >GAP202/10/1333: NoSCoM: Non-Standard Computational Models and Their Applications in Complexity, Linguistics, and Learning</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Machine Learning and Data Mining in Pattern Recognition
ISBN
978-3-642-23198-8
ISSN
—
e-ISSN
—
Number of pages
15
Pages from-to
553-567
Publisher name
Springer
Place of publication
Berlin
Event location
New York
Event date
Aug 30, 2011
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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