Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Last Update2017: administrator
Metadata Last Update2020: administrator
Citation KeyDiasMaDiPeSiNo:2017:HiNeSi
TitleA Hierarchical Network Simplification Via Non-Negative Matrix Factorization
Access Date2021, Jan. 26
Number of Files1
Size1347 KiB
Context area
Author1 Dias, Markus Diego Sampaio da Silva
2 Mansour, Moussa R.
3 Dias, Fabio
4 Petronetto, Fabiano
5 Silva, Cláudio T.
6 Nonato, Luis Gustavo
Affiliation1 Universidade de São Paulo
2 Universidade de São Paulo
3 Universidade de São Paulo
4 Universidade Federal do Espírito Santo
5 New York University
6 Universidade de São Paulo
EditorTorchelsen, Rafael Piccin
Nascimento, Erickson Rangel do
Panozzo, Daniele
Liu, Zicheng
Farias, Mylène
Viera, Thales
Sacht, Leonardo
Ferreira, Nivan
Comba, João Luiz Dihl
Hirata, Nina
Schiavon Porto, Marcelo
Vital, Creto
Pagot, Christian Azambuja
Petronetto, Fabiano
Clua, Esteban
Cardeal, Flávio
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ
DateOct. 17-20, 2017
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2017-08-22 04:04:25 :: -> administrator ::
2020-02-19 02:01:42 :: administrator -> :: 2017
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
Keywordsgraph, matching, simplification, non-negative matrix factorization.
AbstractVisualization tools play an important part in assisting analysts in the understanding of networks and underlying phenomena. However these tasks can be hindered by visual clutter. Simplification/decimation schemes have been a main alternative in this context. Nevertheless, network simplification methods have not been properly evaluated w.r.t. their effectiveness in reducing complexity while preserving relevant structures and content. Moreover, most simplification techniques only consider information extracted from the topology of the network, altogether disregarding additional content. In this work we propose a novel methodology to network simplification that leverages topological information and additional content associated with network elements. The proposed methodology relies on non-negative matrix factorization (NMF) and graph matching, combined to generate a hierarchical representation of the network, grouping the most similar elements in each level of the hierarchy. Moreover, the matrix factorization is only performed at the beginning of the process, reducing the computational cost without compromising the quality of the simplification. The effectiveness of the proposed methodology is assessed through a comprehensive set of quantitative evaluations and comparisons, which shows that our approach outperforms existing simplification methods.
source Directory Contentthere are no files
agreement Directory Content
agreement.html 22/08/2017 01:04 1.2 KiB 
Conditions of access and use area
data URL
zipped data URL
Target FilePID4960567.pdf
Update Permissionnot transferred
Allied materials area
Next Higher Units8JMKD3MGPAW/3PJT9LS
Notes area
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