Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/6422
Título: | Mining approximate motifs in time series |
Autor(es): | Azevedo, Paulo J. Ferreira, Pedro Gabriel Silva, Cândida G. Brito, Rui M. M. |
Palavras-chave: | Bioinformatics Databases |
Data: | 2006 |
Editora: | Springer |
Revista: | Lecture Notes in Computer Science |
Citação: | TODOROVSKI, Ljupco ; LAVRAC, Nada ; JANTKE, Klaus P., ed. lit. – “Discovery science : proceedings of the International Conference of DS-2006, 9, Barcelona, Spain, 2006”. [Berlin] : Springer, 2006. ISBN 3-540-46491-3. |
Resumo(s): | The problem of discovering previously unknown frequent patterns in time series, also called motifs, has been recently introduced. A motif is a subseries pattern that appears a significant number of times. Results demonstrate that motifs may provide valuable insights about the data and have a wide range of applications in data mining tasks. The main motivation for this study was the need to mine time series data from protein folding/unfolding simulations. We propose an algorithm that extracts approximate motifs, i.e. motifs that capture portions of time series with a similar and eventually symmetric behaviour. Preliminary results on the analysis of protein unfolding data support this proposal as a valuable tool. Additional experiments demonstrate that the application of utility of our algorithm is not limited to this particular problem. Rather it can be an interesting tool to be applied in many real world problems. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/6422 |
ISBN: | 3-540-46491-3 |
ISSN: | 0302-9743 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | DI/CCTC - Artigos (papers) |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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DS06-Finalversion_pja.pdf | Documento principal | 200,28 kB | Adobe PDF | Ver/Abrir |