Complex Network Filtering and Compression Algorithm Based on Triangle-Subgraph

Shuxia Ren, Tao Wu and Shubo Zhang

Discrete Dynamics in Nature and Society, 2020, vol. 2020, 1-8

Abstract:

Compressing the data of a complex network is important for visualization. Based on the triangle-subgraph structure in complex networks, complex network filtering compression algorithm based on the triangle-subgraph is proposed. The algorithm starts from the edge, lists nodes of the edge and their common node sets to form a triangle-subgraph set, parses the triangle-subgraph set, and constructs new complex network to complete compression. Before calculating the set of triangle-subgraph, node importance ranking algorithm is proposed to extract high- and low-importance nodes and filter them to reduce computational scale of complex networks. Experimental results show that filtering compression algorithm can not only improve the compression rate but also retain information of the original network at the same time; sorting result analysis and SIR model analysis show that the sorting result of node importance sorting algorithm has accuracy and rationality.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/DDNS/2020/7498605.pdf (application/pdf)
http://downloads.hindawi.com/journals/DDNS/2020/7498605.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:7498605

DOI: 10.1155/2020/7498605

Access Statistics for this article

More articles in Discrete Dynamics in Nature and Society from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().