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» Orthogonal Feature Learning for Time Series Clustering
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PKDD
2001
Springer
185views Data Mining» more  PKDD 2001»
13 years 9 months ago
Temporal Rule Discovery for Time-Series Satellite Images and Integration with RDB
Feature extraction and knowledge discovery from a large amount of image data such as remote sensing images have become highly required recent years. In this study, a framework for ...
Rie Honda, Osamu Konishi
IDA
2003
Springer
13 years 10 months ago
A Semi-supervised Method for Learning the Structure of Robot Environment Interactions
For a mobile robot to act autonomously, it must be able to construct a model of its interaction with the environment. Oates et al. developed an unsupervised learning method that pr...
Axel Großmann, Matthias Wendt, Jeremy Wyatt
CORR
2010
Springer
183views Education» more  CORR 2010»
13 years 3 months ago
Discovering shared and individual latent structure in multiple time series
This paper proposes a nonparametric Bayesian method for exploratory data analysis and feature construction in continuous time series. Our method focuses on understanding shared fe...
Suchi Saria, Daphne Koller, Anna Penn
SDM
2004
SIAM
214views Data Mining» more  SDM 2004»
13 years 6 months ago
Making Time-Series Classification More Accurate Using Learned Constraints
It has long been known that Dynamic Time Warping (DTW) is superior to Euclidean distance for classification and clustering of time series. However, until lately, most research has...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
SSDBM
2006
IEEE
121views Database» more  SSDBM 2006»
13 years 11 months ago
Time Series Analysis Using the Concept of Adaptable Threshold Similarity
The issue of data mining in time series databases is of utmost importance for many practical applications and has attracted a lot of research in the past years. In this paper, we ...
Johannes Aßfalg, Hans-Peter Kriegel, Peer Kr...