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Fundamentalnaya i Prikladnaya Matematika, 2016, Volume 21, Issue 4, Pages 125–132 (Mi fpm1750)  
Data compression in big graph warehouse

I. V. Polyakov, A. A. Chepovskiy, A. M. Chepovskiy

National Research University “The Higher School of Economics,” Moscow, Russia
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Abstract: In this paper, we propose an approach for compact storage of big graphs. We propose preprocessing algorithms for graphs of a certain type, which can significantly increase the data density on the disk and increase performance for basic operations with graphs.
Funding agency Grant number
Russian Foundation for Basic Research 16-07-00641_а
16-29-09546_офи_м
The work was supported by the RFBR grants 16-29-09546 ofi m and 16-07-00641.
English version:
Journal of Mathematical Sciences (New York), 2020, Volume 245, Issue 2, Pages 197–201
DOI: https://doi.org/10.1007/s10958-020-04686-4
Bibliographic databases:
Document Type: Article
UDC: 004.421.2:519.178
Language: Russian
Citation: I. V. Polyakov, A. A. Chepovskiy, A. M. Chepovskiy, “Data compression in big graph warehouse”, Fundam. Prikl. Mat., 21:4 (2016), 125–132; J. Math. Sci., 245:2 (2020), 197–201
Citation in format AMSBIB
\Bibitem{PolCheChe16}
\by I.~V.~Polyakov, A.~A.~Chepovskiy, A.~M.~Chepovskiy
\paper Data compression in big graph warehouse
\jour Fundam. Prikl. Mat.
\yr 2016
\vol 21
\issue 4
\pages 125--132
\mathnet{http://mi.mathnet.ru/fpm1750}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=3783799}
\transl
\jour J. Math. Sci.
\yr 2020
\vol 245
\issue 2
\pages 197--201
\crossref{https://doi.org/10.1007/s10958-020-04686-4}
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    		Фундаментальная и прикладная математика
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