Observatorio de I+D+i UPM

Memorias de investigación
Book chapters:
Comparing Time Series Through Event Clusterin
Year:2008
Research Areas
  • Artificial intelligence
Information
Abstract
The comparison of two time series and the extraction of subsequences that are common to the two is a complex data mining problem. Many existing techniques, like the Discrete Fourier Transform (DFT), offer solutions for comparing two whole time series. Often, however, the important thing is to analyse certain regions, known as events, rather than the whole times series. This applies to domains like the stock market, seismography or medicine. In this paper, we propose a method for comparing two time series by analysing the events present in the two. The proposed method is applied to time series generated by stabilometric and posturographic systems within a branch of medicine studying balancerelated functions in human beings.
International
Si
10.1007/978-3-540-85861-4
Book Edition
0
Book Publishing
Springer Verlag
ISBN
978-3-540-85860-7
Series
Advances in Soft Computing Series
Book title
Innovations in Hybrid Intelligent Systems
From page
1
To page
9
Participants
  • Participante: Juan Alfonso Lara Torralbo (UPM)
  • Autor: Aurora Perez Perez (UPM)
  • Participante: AFRICA LÓPEZ-ILLESCAS (UPM)
  • Autor: Juan Pedro Caraca-Valente Hernandez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Investigación en Tecnología Informática y de las Comunicaciones: CETTICO
  • Departamento: Lenguajes y Sistemas Informáticos e Ingeniería de Software
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