Probabilistic Static Load-Balancing of Parallel Mining of Frequent Sequences

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Probabilistic Static Load-Balancing of Parallel Mining of Frequent Sequences

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Probabilistic Static Load-Balancing of Parallel Mining of Frequent Sequences

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Transactions on Knowledge and Data Engineering

ISSN

1041-4347

e-ISSN

1558-2191

Svazek periodika

28

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

13

Strana od-do

1299-1311

Kód UT WoS článku

000374523000016

EID výsledku v databázi Scopus

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