High-dimensional data hiding pattern mining based on topology data analysis

Authors

Bolong Liu, 1. School of Electrical Engineering, Xinjiang University, Urumqi 830047, China; ;
Zhe Li, 2. Network and Information Technology Center, Xinjiang University, Urumqi 830046, China;

Abstract

Abstract: Aiming at the limitation of traditional data analysis methods to find hidden patterns between high-dimensional complex data, a method of high-dimensional data hiding pattern mining based on topological data analysis is proposed. By extracting the characteristics of complex high-dimensional data, the relationship between its shapes and samples is analyzed. To get the dataset hidden mode, the topological data analysis is used to verify the gender recognition of high-dimensional dataset-voice.. At the same time, the relationship between the dataset data subgroups and related data subgroups is visually analyzed. The results show that the implicit relationship and pattern between data subgroups can be found by the proposed method, which cannot be found by traditional methods and it is more detailed and effective than traditional methods. The results also verify the power and effectiveness of the proposed method for high-dimensional data hiding mode mining.

Recommended Citation

Liu, Bolong and Li, Zhe (2019) "High-dimensional data hiding pattern mining based on topology data analysis," Journal of System Simulation: Vol. 31: Iss. 9, Article 4.
DOI: 10.16182/j.issn1004731x.joss.19-0401
Available at: https://dc-china-simulation.researchcommons.org/journal/vol31/iss9/4

First Page

1755

Revised Date

2019-08-02

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.19-0401

Last Page

1762

CLC

TP391.9

Recommended Citation

Liu Bolong, Li Zhe. High-dimensional data hiding pattern mining based on topology data analysis[J]. Journal of System Simulation, 2019, 31(9): 1755-1762.

DOI

10.16182/j.issn1004731x.joss.19-0401