A New Algorithm and Its Application in Detecting Community of the Bipartite Complex Network
Zhongyi Lei,
Haiying Wang and
Sheng Du
Complexity, 2021, vol. 2021, 1-10
Abstract:
The community division of bipartite networks is one frontier problem on the research of complex networks today. In this study, we propose a model of community detection of the bipartite network, which is based on the generalized suffix tree algorithm. First, extract the adjacent node sequences from the matrix of relation and use the obtained adjacent node sequences to build a generalized suffix tree; second, traverse the established generalized suffix tree to obtain the bipartite cliques; third, adjust the bipartite cliques; finally, dispose the isolated edges, get the communities, and complete the division of the bipartite network. This algorithm is different from the traditional community mining one since it uses edges as the community division medium and does not need to specify the number of the division of communities before the experiment. Furthermore, we can find overlapping communities by this new algorithm which can decrease the time complexity.
Date: 2021
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/complexity/2021/1376609.pdf (application/pdf)
http://downloads.hindawi.com/journals/complexity/2021/1376609.xml (application/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:complx:1376609
DOI: 10.1155/2021/1376609
Access Statistics for this article
More articles in Complexity from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().