A comparative analysis of knowledge acquisition performance in complex networks (2021)
- Authors:
- USP affiliated authors: AMANCIO, DIEGO RAPHAEL - ICMC ; GUERREIRO, LUCAS - ICMC
- Unidade: ICMC
- DOI: 10.1016/j.ins.2020.12.060
- Subjects: REDES COMPLEXAS; DESCOBERTA DE CONHECIMENTO
- Keywords: Knowledge acquistion; Network search; Network dynamics; Random walks
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Information Sciences
- ISSN: 0020-0255
- Volume/Número/Paginação/Ano: v. 555, p. 46-57, May 2021
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
-
ABNT
GUERREIRO, Lucas e SILVA, Filipi Nascimento e AMANCIO, Diego Raphael. A comparative analysis of knowledge acquisition performance in complex networks. Information Sciences, v. 555, p. 46-57, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2020.12.060. Acesso em: 05 jun. 2024. -
APA
Guerreiro, L., Silva, F. N., & Amancio, D. R. (2021). A comparative analysis of knowledge acquisition performance in complex networks. Information Sciences, 555, 46-57. doi:10.1016/j.ins.2020.12.060 -
NLM
Guerreiro L, Silva FN, Amancio DR. A comparative analysis of knowledge acquisition performance in complex networks [Internet]. Information Sciences. 2021 ; 555 46-57.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1016/j.ins.2020.12.060 -
Vancouver
Guerreiro L, Silva FN, Amancio DR. A comparative analysis of knowledge acquisition performance in complex networks [Internet]. Information Sciences. 2021 ; 555 46-57.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1016/j.ins.2020.12.060 - Recovering network topology and dynamics from sequences: a machine learning approach
- Identifying the perceived local properties of networks reconstructed from biased random walks
- Knowledge acquisition and reconstruction in complex networks
- Comparing the topological properties of real and artificially generated scientific manuscripts
- Classificação de textos com redes complexas
- Authorship attribution via network motifs identification
- Labelled network subgraphs reveal stylistic subtleties in written texts
- Authorship recognition via fluctuation analysis of network topology and word intermittency
- Extractive multi document summarization using dynamical measurements of complex networks
- Probing the topological properties of complex networks modeling short written texts
Informações sobre o DOI: 10.1016/j.ins.2020.12.060 (Fonte: oaDOI API)
Download do texto completo
Tipo | Nome | Link | |
---|---|---|---|
3015834.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas