Unsupervised dimensionality reduction for very large datasets: are we going to the right direction? (2020)
- Authors:
- USP affiliated authors: CORDEIRO, ROBSON LEONARDO FERREIRA - ICMC ; OLIVEIRA, JADSON JOSE MONTEIRO - ICMC
- Unidade: ICMC
- DOI: 10.1016/j.knosys.2020.105777
- Subjects: BANCO DE DADOS; MINERAÇÃO DE DADOS; FRACTAIS
- Keywords: Unsupervised dimensionality reduction; Descriptive data mining; Very large datasets; Fractal theory
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Knowledge-Based Systems
- ISSN: 0950-7051
- Volume/Número/Paginação/Ano: v. 196, p. 1-14, May 2020
- Este artigo NÃO possui versão em acesso aberto
-
Status: Nenhuma versão em acesso aberto identificada -
ABNT
OLIVEIRA, Jadson José Monteiro e CORDEIRO, Robson Leonardo Ferreira. Unsupervised dimensionality reduction for very large datasets: are we going to the right direction?. Knowledge-Based Systems, v. 196, p. 1-14, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2020.105777. Acesso em: 11 mar. 2026. -
APA
Oliveira, J. J. M., & Cordeiro, R. L. F. (2020). Unsupervised dimensionality reduction for very large datasets: are we going to the right direction? Knowledge-Based Systems, 196, 1-14. doi:10.1016/j.knosys.2020.105777 -
NLM
Oliveira JJM, Cordeiro RLF. Unsupervised dimensionality reduction for very large datasets: are we going to the right direction? [Internet]. Knowledge-Based Systems. 2020 ; 196 1-14.[citado 2026 mar. 11 ] Available from: https://doi.org/10.1016/j.knosys.2020.105777 -
Vancouver
Oliveira JJM, Cordeiro RLF. Unsupervised dimensionality reduction for very large datasets: are we going to the right direction? [Internet]. Knowledge-Based Systems. 2020 ; 196 1-14.[citado 2026 mar. 11 ] Available from: https://doi.org/10.1016/j.knosys.2020.105777 - Unsupervised Dimensionality Reduction in Big Data via Massive Parallel Processing with MapReduce and Resilient Distributed Datasets
- 'HALITE IND.DS': agrupamento de dados em subespaços de séries temporais multidimensionais
- 'HALITE IND. DS': fast and scalable subspace clustering for multidimensional data streams
- The similarity-aware relational division database operator
- Fast and scalable relational division on database systems
- On the support of the similarity-aware division operator in a commercial RDBMS
- A new division operator to handle complex objects in very large relational datasets
- Fast and scalable outlier detection with metric access methods
- The similarity-aware relational division database operator with case studies in agriculture and genetics
- D.MCA: outlier detection with explicit micro-cluster assignments
Informações sobre a disponibilidade de versões do artigo em acesso aberto coletadas automaticamente via oaDOI API (Unpaywall).
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
| 2995909.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
