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Warped K-Means: An algorithm to cluster sequentially-distributed data

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Warped K-Means: An algorithm to cluster sequentially-distributed data

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Leiva Torres, LA.; Vidal, E. (2013). Warped K-Means: An algorithm to cluster sequentially-distributed data. Information Sciences. 237:196-210. doi:10.1016/j.ins.2013.02.042

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/38225

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Title: Warped K-Means: An algorithm to cluster sequentially-distributed data
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Universitat Politècnica de València. Instituto Universitario Mixto Tecnológico de Informática - Institut Universitari Mixt Tecnològic d'Informàtica
Issued date:
Abstract:
[EN] Many devices generate large amounts of data that follow some sort of sequentiality, e.g., motion sensors, e-pens, eye trackers, etc. and often these data need to be compressed for classification, storage, and/or ...[+]
Subjects: Partitional clustering , Sequential data , Trajectory segmentation , Data compression , Data simplification
Copyrigths: Reserva de todos los derechos
Source:
Information Sciences. (issn: 0020-0255 )
DOI: 10.1016/j.ins.2013.02.042
Publisher:
Elsevier
Publisher version: http://dx.doi.org/10.1016/j.ins.2013.02.042
Project ID: info:eu-repo/grantAgreement/EC/FP7/287576 info:eu-repo/grantAgreement/EC/FP7/600707
Thanks:
This work has been partially supported by Casmacat (FP7-ICT-2011-7, Project 287576), tranScriptorium (FP7-ICT-2011-9, Project 600707), STraDA (MINECO, TIN2012-37475-0O2-01), and ALMPR (GVA, Prometeo/20091014) projects.
Type: Artículo

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