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» Association Rules Discovery in Multivariate Time Series
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JMLR
2010
194views more  JMLR 2010»
13 years 2 months ago
Graphical Gaussian modelling of multivariate time series with latent variables
In time series analysis, inference about causeeffect relationships among multiple times series is commonly based on the concept of Granger causality, which exploits temporal struc...
Michael Eichler
MMDB
2004
ACM
153views Multimedia» more  MMDB 2004»
14 years 27 days ago
A PCA-based similarity measure for multivariate time series
Multivariate time series (MTS) datasets are common in various multimedia, medical and financial applications. We propose a similarity measure for MTS datasets, Eros (Extended Fro...
Kiyoung Yang, Cyrus Shahabi
AIME
2007
Springer
14 years 1 months ago
A Human-Machine Cooperative Approach for Time Series Data Interpretation
Abstract. This paper deals with the interpretation of biomedical multivariate time series for extracting typical scenarios. This task is known to be difficult, due to the temporal ...
Thomas Guyet, Catherine Garbay, Michel Dojat
AAAI
2007
13 years 9 months ago
Discovering Multivariate Motifs using Subsequence Density Estimation and Greedy Mixture Learning
The problem of locating motifs in real-valued, multivariate time series data involves the discovery of sets of recurring patterns embedded in the time series. Each set is composed...
David Minnen, Charles Lee Isbell Jr., Irfan A. Ess...
ICSE
2010
IEEE-ACM
14 years 8 days ago
An eclectic approach for change impact analysis
Change impact analysis aims at identifying software artifacts being affected by a change. In the past, this problem has been addressed by approaches relying on static, dynamic, a...
Michele Ceccarelli, Luigi Cerulo, Gerardo Canfora,...