Reference TypeConference Proceedings
Citation KeyDiasValdPetrNona:2018:GrSpFi
Author1 Dias, Markus Diego Sampaio da Silva
2 Valdivia, Paola
3 Petronetto, Fabiano
4 Nonato, Luis Gustavo
Affiliation1 Universidade de São Paulo
2 Universidade de São Paulo
3 Universidade Federal do Espírito Santo
4 Universidade de São Paulo
TitleGraph Spectral Filtering for Network Simplification
Conference NameConference on Graphics, Patterns and Images, 31 (SIBGRAPI)
EditorRoss, Arun
Gastal, Eduardo S. L.
Jorge, Joaquim A.
Queiroz, Ricardo L. de
Minetto, Rodrigo
Sarkar, Sudeep
Papa, João Paulo
Oliveira, Manuel M.
Arbeláez, Pablo
Mery, Domingo
Oliveira, Maria Cristina Ferreira de
Spina, Thiago Vallin
Mendes, Caroline Mazetto
Costa, Henrique Sérgio Gutierrez
Mejail, Marta Estela
Geus, Klaus de
Scheer, Sergio
Book TitleProceedings
DateOct. 29 - Nov. 1, 2018
Publisher CityLos Alamitos
PublisherIEEE Computer Society
Conference LocationFoz do Iguaçu, PR, Brazil
Keywordsnetwork, graph signal processing, spectral filtering, network simplification, visualization.
AbstractVisualization is an important tool in the analysis and understanding of networks and their content. However, visualization tools face major challenges when dealing with large networks, mainly due to visual clutter. In this context, network simplification has been a main alternative to handle massive networks, reducing complexity while preserving relevant patterns of the network structure and content. In this paper we propose a methodology that rely on Graph Signal Processing theory to filter multivariate data associated to network nodes, assisting and enhancing network simplification and visualization tasks. The simplification process takes into account both topological and multivariate data associated to network nodes to create a hierarchical representation of the network. The effectiveness of the proposed methodology is assessed through a comprehensive set of quantitative evaluation and comparisons, which gauge the impact of the proposed filtering process in the simplification and visualization tasks.
Tertiary TypeFull Paper
Size5806 KiB
Number of Files1
Target FilePaper ID 70.pdf
Last Update2018: administrator
Metadata Last Update2020: administrator {D 2018}
Document Stagecompleted
Is the master or a copy?is the master
Content TypeExternal Contribution
Document Stagenot transferred
Next Higher Units8JMKD3MGPAW/3RPADUS
source Directory Contentthere are no files
agreement Directory Content
agreement.html 03/09/2018 16:21 1.2 KiB 
History2018-09-03 19:21:15 :: -> administrator ::
2020-02-19 03:10:44 :: administrator -> :: 2018
Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume
Access Date2020, Nov. 29