@InProceedings{DiasMaDiPeSiNo:2017:HiNeSi,
author = "Dias, Markus Diego Sampaio da Silva and Mansour, Moussa R. and
Dias, Fabio and Petronetto, Fabiano and Silva, Cl{\'a}udio T. and
Nonato, Luis Gustavo",
affiliation = "{Universidade de S{\~a}o Paulo} and {Universidade de S{\~a}o
Paulo} and {Universidade de S{\~a}o Paulo} and {Universidade
Federal do Esp{\'{\i}}rito Santo} and {New York University} and
{Universidade de S{\~a}o Paulo}",
title = "A Hierarchical Network Simplification Via Non-Negative Matrix
Factorization",
booktitle = "Proceedings...",
year = "2017",
editor = "Torchelsen, Rafael Piccin and Nascimento, Erickson Rangel do and
Panozzo, Daniele and Liu, Zicheng and Farias, Myl{\`e}ne and
Viera, Thales and Sacht, Leonardo and Ferreira, Nivan and Comba,
Jo{\~a}o Luiz Dihl and Hirata, Nina and Schiavon Porto, Marcelo
and Vital, Creto and Pagot, Christian Azambuja and Petronetto,
Fabiano and Clua, Esteban and Cardeal, Fl{\'a}vio",
organization = "Conference on Graphics, Patterns and Images, 30. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "graph, matching, simplification, non-negative matrix
factorization.",
abstract = "Visualization 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.",
conference-location = "Niter{\'o}i, RJ, Brazil",
conference-year = "17-20 Oct. 2017",
doi = "10.1109/SIBGRAPI.2017.22",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2017.22",
language = "en",
ibi = "8JMKD3MGPAW/3PFSGP8",
url = "http://urlib.net/ibi/8JMKD3MGPAW/3PFSGP8",
targetfile = "PID4960567.pdf",
urlaccessdate = "2024, May 02"
}