An efficient graph data compression model based on the germ quotient set structure

Dawei WANG, Wanqiu CUI

PDF(1070 KB)
PDF(1070 KB)
Front. Comput. Sci. ›› 2022, Vol. 16 ›› Issue (6) : 166617. DOI: 10.1007/s11704-022-1489-7
Information Systems
LETTER

An efficient graph data compression model based on the germ quotient set structure

Author information +
History +

Graphical abstract

Cite this article

Download citation ▾
Dawei WANG, Wanqiu CUI. An efficient graph data compression model based on the germ quotient set structure. Front. Comput. Sci., 2022, 16(6): 166617 https://doi.org/10.1007/s11704-022-1489-7

References

[1]
Park C S , Kaye B K . The tweet goes on: interconnection of twitter opinion leadership, network size, and civic engagement. Computers in Human Behavior, 2017, 69: 174– 180
[2]
Delgosha P , Anantharam V . Universal lossless compression of graphical data. IEEE Transactions on Information Theory, 2020, 66( 11): 6962– 6976
[3]
Xue Z , Du J , Du D , Lyu S . Deep low-rank subspace ensemble for multi-view clustering. Information Science, 2019, 482: 210– 227
[4]
Lu F , Kothari N , Feng X , Zhang L . Equivalence classes in matching covered graphs. Discrete Mathematics, 2020, 343( 8): 111945
[5]
Robinson I Webber J Eifrem E. Graph Databases. 2nd ed. California: O’Reilly Media Inc, 2015

Acknowledgements

This work was supported by the ISTIC Innovation Research Foundation (QN2022-05), by the National Natural Science Foundation of China (NSFC) (Grant No. 72074201), and sponsored by the National Social Science Foundation of China (NSSFC) (21CTQ039).

RIGHTS & PERMISSIONS

2022 Higher Education Press
AI Summary AI Mindmap
PDF(1070 KB)

Accesses

Citations

Detail

Sections
Recommended

/