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Development of parallel FRiS-Tax text document clustering algorithm based on MPI technology. / Mansurova, M. E.; Barakhnin, V. B.; Aubakirov, S. S. и др.

в: CEUR Workshop Proceedings, Том 1576, 2016, стр. 244-256.

Результаты исследований: Научные публикации в периодических изданиях › статья по материалам конференции › Рецензирование

Harvard

Mansurova, ME, Barakhnin, VB, Aubakirov, SS, Khibatkhanuly, Y & Mussina, AB 2016, 'Development of parallel FRiS-Tax text document clustering algorithm based on MPI technology', CEUR Workshop Proceedings, Том. 1576, стр. 244-256.

APA

Mansurova, M. E., Barakhnin, V. B., Aubakirov, S. S., Khibatkhanuly, Y., & Mussina, A. B. (2016). Development of parallel FRiS-Tax text document clustering algorithm based on MPI technology. CEUR Workshop Proceedings, 1576, 244-256.

Vancouver

Mansurova ME, Barakhnin VB, Aubakirov SS, Khibatkhanuly Y, Mussina AB. Development of parallel FRiS-Tax text document clustering algorithm based on MPI technology. CEUR Workshop Proceedings. 2016;1576:244-256.

Author

Mansurova, M. E. ; Barakhnin, V. B. ; Aubakirov, S. S. и др. / Development of parallel FRiS-Tax text document clustering algorithm based on MPI technology. в: CEUR Workshop Proceedings. 2016 ; Том 1576. стр. 244-256.

BibTeX

@article{34b3fbc47a8644c8b42cb7c5991756f4,
title = "Development of parallel FRiS-Tax text document clustering algorithm based on MPI technology",
abstract = "This paper describes a parallel implementation of FRiS-Tax text document clustering algorithm. The clustering algorithm is based on an assessment of the similarity between objects in the competitive situation that leads to the concept of competitive similarity function (FRiS-function). As the scales for determination of the similarity measures are selected attributes of bibliographic description of documents. The parallelization is performed on the step of coefficient tuning in similarity measure formula of the genetic algorithm, as well as directly in step of clustering. The clustering algorithm is implemented on a highperformance MPJ Express platform. Quantitative evaluation of the execution time of the process is performed, clearly demonstrating the advantages of parallel implementation of the algorithm.",
keywords = "Clustering text documents, Genetic algorithms, Parallel algorithms",
author = "Mansurova, {M. E.} and Barakhnin, {V. B.} and Aubakirov, {S. S.} and Ye Khibatkhanuly and Mussina, {A. B.}",
year = "2016",
language = "English",
volume = "1576",
pages = "244--256",
journal = "CEUR Workshop Proceedings",
issn = "1613-0073",
publisher = "CEUR-WS",
note = "10th Annual International Scientific Conference on Parallel Computing Technologies, PCT 2016 ; Conference date: 29-03-2016 Through 31-03-2016",

}

RIS

TY - JOUR

T1 - Development of parallel FRiS-Tax text document clustering algorithm based on MPI technology

AU - Mansurova, M. E.

AU - Barakhnin, V. B.

AU - Aubakirov, S. S.

AU - Khibatkhanuly, Ye

AU - Mussina, A. B.

PY - 2016

Y1 - 2016

N2 - This paper describes a parallel implementation of FRiS-Tax text document clustering algorithm. The clustering algorithm is based on an assessment of the similarity between objects in the competitive situation that leads to the concept of competitive similarity function (FRiS-function). As the scales for determination of the similarity measures are selected attributes of bibliographic description of documents. The parallelization is performed on the step of coefficient tuning in similarity measure formula of the genetic algorithm, as well as directly in step of clustering. The clustering algorithm is implemented on a highperformance MPJ Express platform. Quantitative evaluation of the execution time of the process is performed, clearly demonstrating the advantages of parallel implementation of the algorithm.

AB - This paper describes a parallel implementation of FRiS-Tax text document clustering algorithm. The clustering algorithm is based on an assessment of the similarity between objects in the competitive situation that leads to the concept of competitive similarity function (FRiS-function). As the scales for determination of the similarity measures are selected attributes of bibliographic description of documents. The parallelization is performed on the step of coefficient tuning in similarity measure formula of the genetic algorithm, as well as directly in step of clustering. The clustering algorithm is implemented on a highperformance MPJ Express platform. Quantitative evaluation of the execution time of the process is performed, clearly demonstrating the advantages of parallel implementation of the algorithm.

KW - Clustering text documents

KW - Genetic algorithms

KW - Parallel algorithms

UR - http://www.scopus.com/inward/record.url?scp=84978472800&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:84978472800

VL - 1576

SP - 244

EP - 256

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

T2 - 10th Annual International Scientific Conference on Parallel Computing Technologies, PCT 2016

Y2 - 29 March 2016 through 31 March 2016

ER -

ID: 25326562