Organizational data classification based on the importance concept of complex networks (2018)
- Authors:
- Autor USP: LIANG, ZHAO - FFCLRP
- Unidade: FFCLRP
- DOI: 10.1109/TNNLS.2017.2726082
- Subjects: REDES COMPLEXAS; APRENDIZADO COMPUTACIONAL; RECONHECIMENTO DE PADRÕES
- Keywords: Complex networks; Data classification; Importance based; Network-based learning; PageRank
- Language: Inglês
- Imprenta:
- Publisher place: Piscataway
- Date published: 2018
- Source:
- Título: IEEE Transactions on Neural Networks and Learning Systems
- ISSN: 2162-237X
- Volume/Número/Paginação/Ano: v. 29, n. 8, p. 3361-3373, 2018
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
CARNEIRO, Murillo Guimarães e LIANG, Zhao. Organizational data classification based on the importance concept of complex networks. IEEE Transactions on Neural Networks and Learning Systems, v. 29, n. 8, p. 3361-3373, 2018Tradução . . Disponível em: https://doi.org/10.1109/TNNLS.2017.2726082. Acesso em: 09 jan. 2026. -
APA
Carneiro, M. G., & Liang, Z. (2018). Organizational data classification based on the importance concept of complex networks. IEEE Transactions on Neural Networks and Learning Systems, 29( 8), 3361-3373. doi:10.1109/TNNLS.2017.2726082 -
NLM
Carneiro MG, Liang Z. Organizational data classification based on the importance concept of complex networks [Internet]. IEEE Transactions on Neural Networks and Learning Systems. 2018 ; 29( 8): 3361-3373.[citado 2026 jan. 09 ] Available from: https://doi.org/10.1109/TNNLS.2017.2726082 -
Vancouver
Carneiro MG, Liang Z. Organizational data classification based on the importance concept of complex networks [Internet]. IEEE Transactions on Neural Networks and Learning Systems. 2018 ; 29( 8): 3361-3373.[citado 2026 jan. 09 ] Available from: https://doi.org/10.1109/TNNLS.2017.2726082 - Data heterogeneity consideration in semi-supervised learning
- Machine learning via dynamical processes in complex networks
- Semi-supervised learning guided by the modularity measure in complex networks
- Handwritten digits recognition using a high level network-based approach
- On the data classification using complex network entropy
- Caracterização de classes via otimização em redes complexas
- Network-based supervised data classification by using an heuristic of ease of access
- Label propagation through neuronal synchrony
- QK-means: a clustering technique based on community detection and 'capa'-means for deployment of custer head nodes
- Attraction forces based semi-supervised learning
Informações sobre o DOI: 10.1109/TNNLS.2017.2726082 (Fonte: oaDOI API)
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