DOMINANT EIGENVECTOR AND EIGENVALUE ALGORITHM IN SPARSE NETWORK SPECTRAL CLUSTERING

Authors

  • B. J. YANG

DOI:

https://doi.org/10.52292/j.laar.2018.248

Keywords:

sparse network spectrum, clustering, dominant eigenvector, eigenvalue

Abstract

The sparse network spectrum clustering problem is studied in this paper. It tries to analyze and improve the sparse network spectrum clustering algorithm from the main feature pair algorithm. The main feature pair algorithm in the matrix calculation is combined with the spectral clustering algorithm to explore the application of the main feature pair algorithm on the network adjacency matrix. The defects of traditional main features are analyzed when the algorithm Power is used on the network of special structural features, and the advantages of the new algorithm SII algorithm is proved. The sparse network spectral clustering algorithm in this paper is based on the Score algorithm, and the main features of the algorithm are refined, analyzed and improved.

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Published

2018-10-31

Issue

Vol. 48 No. 4 (2018): Latin American Applied Research

Section

Control and Information Processing

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