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ECML
1997
Springer
13 years 8 months ago
Parallel and Distributed Search for Structure in Multivariate Time Series
Abstract. E cient data mining algorithms are crucial fore ective knowledge discovery. We present the Multi-Stream Dependency Detection (msdd) data mining algorithm that performs a ...
Tim Oates, Matthew D. Schmill, Paul R. Cohen
AAAI
2000
13 years 5 months ago
Multivariate Clustering by Dynamics
We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a tim...
Marco Ramoni, Paola Sebastiani, Paul R. Cohen
MMDB
2004
ACM
153views Multimedia» more  MMDB 2004»
13 years 9 months 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
KDD
2009
ACM
364views Data Mining» more  KDD 2009»
14 years 4 months ago
Causality quantification and its applications: structuring and modeling of multivariate time series
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
Takashi Shibuya, Tatsuya Harada, Yasuo Kuniyoshi
IDA
2003
Springer
13 years 9 months ago
Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies
Abstract. Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any mode...
Allan Tucker, Xiaohui Liu