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ISNN
2011
Springer
14 years 17 days ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
102
Voted
SDM
2010
SIAM
202views Data Mining» more  SDM 2010»
14 years 8 months ago
Multiresolution Motif Discovery in Time Series
Time series motif discovery is an important problem with applications in a variety of areas that range from telecommunications to medicine. Several algorithms have been proposed t...
Nuno Castro, Paulo J. Azevedo
SDM
2004
SIAM
214views Data Mining» more  SDM 2004»
14 years 11 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
IDA
2003
Springer
15 years 2 months ago
Fuzzy Clustering Based Segmentation of Time-Series
The segmentation of time-series is a constrained clustering problem: the data points should be grouped by their similarity, but with the constraint that all points in a cluster mus...
János Abonyi, Balazs Feil, Sandor Z. N&eacu...
CGF
2011
14 years 1 months ago
Visual Exploration of Time-Series Data with Shape Space Projections
Time-series data is a common target for visual analytics, as they appear in a wide range of application domains. Typical tasks in analyzing time-series data include identifying cy...
Matthew O. Ward, Zhenyu Guo