Probabilistic Static Load-Balancing of Parallel Mining of Frequent Sequences
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F16%3A00338693" target="_blank" >RIV/68407700:21240/16:00338693 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/TKDE.2016.2515622" target="_blank" >https://doi.org/10.1109/TKDE.2016.2515622</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TKDE.2016.2515622" target="_blank" >10.1109/TKDE.2016.2515622</a>
Alternative languages
Result language
angličtina
Original language name
Probabilistic Static Load-Balancing of Parallel Mining of Frequent Sequences
Original language description
Frequent sequence mining is well known and well studied problem in datamining. The output of the algorithm is used in many other areas like bioinformatics, chemistry, and market basket analysis. Unfortunately, the frequent sequence mining is computationally quite expensive. In this paper, we present a novel parallel algorithm for mining of frequent sequences based on a static load-balancing. The static load-balancing is done by measuring the computational time using a probabilistic algorithm. For reasonable size of instance, the algorithms achieve speedups up to approximate to 3/4 . P where P is the number of processors. In the experimental evaluation, we show that our method performs significantly better then the current state-of-the-art methods. The presented approach is very universal: it can be used for static load-balancing of other pattern mining algorithms such as itemset/tree/graph mining algorithms.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Transactions on Knowledge and Data Engineering
ISSN
1041-4347
e-ISSN
1558-2191
Volume of the periodical
28
Issue of the periodical within the volume
5
Country of publishing house
US - UNITED STATES
Number of pages
13
Pages from-to
1299-1311
UT code for WoS article
000374523000016
EID of the result in the Scopus database
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