A comparative analysis of local similarity metrics and machine learning approaches: application to link prediction in author citation networks (2022)
- Authors:
- USP affiliated authors: AMANCIO, DIEGO RAPHAEL - ICMC ; VITAL JUNIOR, ADILSON - ICMC
- Unidade: ICMC
- DOI: 10.1007/s11192-022-04484-6
- Subjects: CIENTOMETRIA; BIBLIOMETRIA; APRENDIZADO COMPUTACIONAL
- Keywords: Link prediction; Citation networks; Network similarity; Science of science; Authors citation networks
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Scientometrics
- ISSN: 0138-9130
- Volume/Número/Paginação/Ano: v. 127, n. 10, p. 6011-6028, Oct. 2022
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
VITAL, Adilson e AMANCIO, Diego Raphael. A comparative analysis of local similarity metrics and machine learning approaches: application to link prediction in author citation networks. Scientometrics, v. 127, n. 10, p. 6011-6028, 2022Tradução . . Disponível em: https://doi.org/10.1007/s11192-022-04484-6. Acesso em: 06 jun. 2025. -
APA
Vital, A., & Amancio, D. R. (2022). A comparative analysis of local similarity metrics and machine learning approaches: application to link prediction in author citation networks. Scientometrics, 127( 10), 6011-6028. doi:10.1007/s11192-022-04484-6 -
NLM
Vital A, Amancio DR. A comparative analysis of local similarity metrics and machine learning approaches: application to link prediction in author citation networks [Internet]. Scientometrics. 2022 ; 127( 10): 6011-6028.[citado 2025 jun. 06 ] Available from: https://doi.org/10.1007/s11192-022-04484-6 -
Vancouver
Vital A, Amancio DR. A comparative analysis of local similarity metrics and machine learning approaches: application to link prediction in author citation networks [Internet]. Scientometrics. 2022 ; 127( 10): 6011-6028.[citado 2025 jun. 06 ] Available from: https://doi.org/10.1007/s11192-022-04484-6 - Comparing random walks in graph embedding and link prediction
- 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
- Comparing the topological properties of real and artificially generated scientific manuscripts
- Probing the topological properties of complex networks modeling short written texts
- Network analysis of named entity co-occurrences in written texts
- A complex network approach to stylometry
Informações sobre o DOI: 10.1007/s11192-022-04484-6 (Fonte: oaDOI API)
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