On the use of aggregation functions for semi-supervised network embedding (2023)
- Authors:
- USP affiliated authors: MARCACINI, RICARDO MARCONDES - ICMC ; MORAES JUNIOR, MARCELO ISAIAS DE - ICMC
- Unidade: ICMC
- DOI: 10.1109/IJCNN54540.2023.10191468
- Subjects: REDES NEURAIS; APRENDIZADO COMPUTACIONAL
- Keywords: Network Embedding; Graph Neural Networks; Semi-Supervised Learning; Aggregation Functions
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2023
- Source:
- Título: Proceedings
- Conference titles: International Joint Conference on Neural Networks - IJCNN
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
MORAES JUNIOR, Marcelo Isaias de e MARCACINI, Ricardo Marcondes. On the use of aggregation functions for semi-supervised network embedding. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/IJCNN54540.2023.10191468. Acesso em: 13 fev. 2026. -
APA
Moraes Junior, M. I. de, & Marcacini, R. M. (2023). On the use of aggregation functions for semi-supervised network embedding. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN54540.2023.10191468 -
NLM
Moraes Junior MI de, Marcacini RM. On the use of aggregation functions for semi-supervised network embedding [Internet]. Proceedings. 2023 ;[citado 2026 fev. 13 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191468 -
Vancouver
Moraes Junior MI de, Marcacini RM. On the use of aggregation functions for semi-supervised network embedding [Internet]. Proceedings. 2023 ;[citado 2026 fev. 13 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191468 - Unsupervised heterogeneous graph neural networks for one-class tasks: exploring early fusion operators
- On the use of early fusion operators on heterogeneous graph neural networks for one-class learning
- BEATS: search engine for architectural strategies for security
- Complaint analysis in fintech domain: a case study in Brazilian brokerage firms
- Aprendizado de máquina com informação privilegiada: abordagens para agrupamento hierárquico de textos
- Aprendizado não supervisionado de hierarquias de tópicos a partir de coleções textuais dinâmicas
- MApp-IDEA: design and architecture of the analytical data exploration tool from app reviews
- PPM-HC: a method for helping project portfolio management based on topic hierarchy learnings
- Proceendings of 19th National Meeting on Artificial and Computational Intelligence
- Named Entity Recognition approaches applied to legal document segmentation
Informações sobre o DOI: 10.1109/IJCNN54540.2023.10191468 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3150800.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
