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

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

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.

Key words: topological data analysis, hidden pattern mining, high dimensional data

CLC Number:

TP391.9

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.

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