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Record type:	stať ve sborníku (D)
Home Department:	Ústav pro výzkum a aplikace fuzzy modelování (94410)
Title:	Parallel Mining of Fuzzy Association Rules on Dense Data Sets
Citace	Burda, M., Pavliska, V. a Valášek, R. Parallel Mining of Fuzzy Association Rules on Dense Data Sets. In: IEEE International Conference on Fuzzy Systems. Beijing, China: IEEE, 2014. IEEE, 2014. s. 2156-2162. ISBN 978-1-4799-2072-3.

Subtitle
Publication year:	2014
Obor:	Informatika
Number of pages:	7
Page from:	2156
Page to:	2162
Form of publication:	Tištená verze
ISBN code:	978-1-4799-2072-3
ISSN code:	1098-7584
Proceedings title:	IEEE International Conference on Fuzzy Systems
Proceedings:	Mezinárodní
Publisher name:	IEEE
Place of publishing:	Beijing, China
Country of Publication:	Sborník vydaný v zahraničí
Název konference:	IEEE International Conference on Fuzzy Systems
Místo konání konference:	Beijing, China
Datum zahájení konference:
Typ akce podle státní příslušnosti účastníků:	Celosvětová akce
WoS code:
EID:

Key words in English:	fuzzy association rules opus algorithm parallelization
Annotation in original language:	The aim of this paper is to present a scalable parallel algorithm for fuzzy association rules mining that is suitable for dense data sets. Unlike most of other approaches, we have based the algorithm on the Webb's OPUS search algorithm. Having adopted the master/slave architecture, we propose a simple recursion threshold technique to allow load-balancing for high scalability.
Annotation in english language:

References

Reference

R01:	RIV/61988987:17610/14:A1501BDK

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