Correlated trends: a new representation for imperfect and large dataseries
LNCS, International Conference on Flexible Query Answering Systems 2013
8132
, pp. 305–316
(2013)
Abstract:
The computational representation of dataseries is a task of growing interest in our days. However, as these data are often imperfect, new representation models are required to effectively handle them. This work presents Frequent Correlated Trends, our proposal for representing uncertain and imprecise multivariate dataseries. Such a model can be applied to any domain where dataseries contain patterns that recur in similar —but not identical— shape. We describe here the model representation and an associated learning algorithm.
Links:
| DOI: 10.1007/978-3-642-40769-7_27 PDF: |
Bibtex:
@incollection{FQAS2013_Delgado,
title = {Correlated trends: a new representation for imperfect and large dataseries},
author = {Delgado, Miguel and Fajardo, Waldo and Molina-Solana, Miguel},
booktitle = {LNCS, International Conference on Flexible Query Answering Systems 2013},
publisher = {Springer Berlin Heidelberg},
year = {2013},
address = {Granada, Spain},
month = sep,
pages = {305--316},
series = {Lecture Notes in Computer Science},
volume = {8132},
pdf = {},
doi = {10.1007/978-3-642-40769-7_27},
timestamp = {111},
url = {http://idbis.ugr.es/fqas2013/}
}