| Full text | |
| Author(s): Show less - |
Nogueira Lorena, Luiz Henrique
;
Quiles, Marcos Goncalves
;
Nogueira Lorena, Luiz Antonio
;
Misra, S
;
Gervasi, O
;
Murgante, B
;
Stankova, E
;
Korkhov, V
;
Torre, C
;
Rocha, AMAC
;
Taniar, D
;
Apduhan, BO
;
Tarantino, E
Total Authors: 13
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| Document type: | Journal article |
| Source: | COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2019, PT I; v. 11619, p. 13-pg., 2019-01-01. |
| Abstract | |
Different fields of science use network representation as a framework to model their systems. The analysis of network structure can give us essential information about the system. However, the size of such a network can limit the applicability of some fundamental techniques like mathematical programming. Thus, here we propose a novel network size reduction technique based on a clique filtering approach. Our goal is twofold: (1) reduce the network size and speed up the community detection process, and (2) preserve the modularity of the original partition in the context of the exact model. Conducted experiments show the feasibility and correctness of the proposed technique. (AU) | |
| FAPESP's process: | 15/50122-0 - Dynamic phenomena in complex networks: basics and applications |
| Grantee: | Elbert Einstein Nehrer Macau |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 11/18496-7 - Dynamic semi-supervised and active learning based on complex networks |
| Grantee: | Marcos Gonçalves Quiles |
| Support Opportunities: | Research Grants - Young Investigators Grants |