Skip to Main content Skip to Navigation
Conference papers

On Spectral Partitioning of Co-authorship Networks

Abstract : Spectral partitioning is a well known method in the area of graph and matrix analysis. Several approaches based on spectral partitioning and spectral clustering were used to detect structures in real world networks and databases. In this paper, we explore two community detection approaches based on the spectral partitioning to analyze a co-authorship network. The partitioning exploits the concepts of algebraic connectivity and characteristic valuation to form components useful for the analysis of relations and communities in real world social networks.
Complete list of metadatas

Cited literature [18 references]  Display  Hide  Download

https://hal.inria.fr/hal-01551743
Contributor : Hal Ifip <>
Submitted on : Friday, June 30, 2017 - 2:43:29 PM
Last modification on : Saturday, June 1, 2019 - 11:34:02 AM
Long-term archiving on: : Monday, January 22, 2018 - 8:05:55 PM

File

978-3-642-33260-9_26_Chapter.p...
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Václav Snášel, Pavel Krömer, Jan Platoš, Miloš Kudělka, Zdeněk Horák. On Spectral Partitioning of Co-authorship Networks. 11th International Conference on Computer Information Systems and Industrial Management (CISIM), Sep 2012, Venice, Italy. pp.302-313, ⟨10.1007/978-3-642-33260-9_26⟩. ⟨hal-01551743⟩

Share

Metrics

Record views

157

Files downloads

354