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SDM
2004
SIAM
214views Data Mining» more  SDM 2004»
13 years 7 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
SIGMOD
2001
ACM
184views Database» more  SIGMOD 2001»
14 years 6 months ago
Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases
Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because of the typically high dimensionality of the data....
Eamonn J. Keogh, Kaushik Chakrabarti, Sharad Mehro...
AUSDM
2008
Springer
274views Data Mining» more  AUSDM 2008»
13 years 8 months ago
Identifying Stock Similarity Based on Multi-event Episodes
Predicting stock market movements is always difficult. Investors try to guess a stock's behavior, but it often backfires. Thumb rules and intuition seems to be the major indi...
Abhi Dattasharma, Praveen Kumar Tripathi, Sridhar ...
SDM
2008
SIAM
97views Data Mining» more  SDM 2008»
13 years 7 months ago
Efficient Distribution Mining and Classification
We define and solve the problem of "distribution classification", and, in general, "distribution mining". Given n distributions (i.e., clouds) of multi-dimensi...
Yasushi Sakurai, Rosalynn Chong, Lei Li, Christos ...
ICDM
2010
IEEE
99views Data Mining» more  ICDM 2010»
13 years 4 months ago
A System for Mining Temporal Physiological Data Streams for Advanced Prognostic Decision Support
We present a mining system that can predict the future health status of the patient using the temporal trajectories of health status of a set of similar patients. The main noveltie...
Jimeng Sun, Daby Sow, Jianying Hu, Shahram Ebadoll...