Informativity-based graph: exploring mutual kNN and labeled vertices for semi-supervised learning (2012)
- Authors:
- Autor USP: LOPES, ALNEU DE ANDRADE - ICMC
- Unidade: ICMC
- DOI: 10.1109/CASoN.2012.6412371
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2012
- ISBN: 9781467347921
- Source:
- Título do periódico: Proceedings
- Conference titles: International Conference on Computational Aspects of Social Networks - CASoN
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
BERTON, Lilian; LOPES, Alneu de Andrade. Informativity-based graph: exploring mutual kNN and labeled vertices for semi-supervised learning. Anais.. Piscataway: IEEE, 2012.Disponível em: -
APA
Berton, L., & Lopes, A. de A. (2012). Informativity-based graph: exploring mutual kNN and labeled vertices for semi-supervised learning. In Proceedings. Piscataway: IEEE. doi:10.1109/CASoN.2012.6412371 -
NLM
Berton L, Lopes A de A. Informativity-based graph: exploring mutual kNN and labeled vertices for semi-supervised learning [Internet]. Proceedings. 2012 ;Available from: http://dx.doi.org/10.1109/CASoN.2012.6412371 -
Vancouver
Berton L, Lopes A de A. Informativity-based graph: exploring mutual kNN and labeled vertices for semi-supervised learning [Internet]. Proceedings. 2012 ;Available from: http://dx.doi.org/10.1109/CASoN.2012.6412371 - Efficient identification of duplicate bibliographical references
- Information extraction from tagged bibliographical references
- A graph-based bagging
- Exploring data classification with k-associated network
- Bipartite graph for topic extraction
- Network sampling based on centrality measures for relational classification
- Data visualization and relevance feedback applied to information retrieval
- An open source tool for crowd-sourcing the manual annotation of texts
- Link prediction in graph construction for supervised and semi-supervised learning
- Structural link prediction using community information on Twitter
Informações sobre o DOI: 10.1109/CASoN.2012.6412371 (Fonte: oaDOI API)
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
