Title Time series clustering based on the characterisation of segment typologies
Authors Guijo Rubio, David , DURAN ROSAL, ANTONIO MANUEL, Gutiérrez Peña, Pedro Antonio , Troncoso, Alicia , Hervás Martínez, César
External publication No
Means IEEE Trans. Cybern.
Scope Article
Nature Científica
JCR Quartile 1
SJR Quartile 1
JCR Impact 11.44800
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119434666&doi=10.1109%2fTCYB.2019.2962584&partnerID=40&md5=efc7d3cc299735184e7f138683829e0f
Publication date 15/01/2020
ISI 000716697700022
Scopus Id 2-s2.0-85119434666
DOI 10.1109/TCYB.2019.2962584
Abstract Time-series clustering is the process of grouping time series with respect to their similarity or characteristics. Previous approaches usually combine a specific distance measure for time series and a standard clustering method. However, these approaches
Keywords Time series analysis; Hidden Markov models; Clustering algorithms; Time measurement; Autoregressive processes; Data mining; Proposals; Data mining; feature extraction; segmentation; time-series cluste
Universidad Loyola members

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