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» Finding the most unusual time series subsequence: algorithms...
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KDD
2009
ACM
192views Data Mining» more  KDD 2009»
14 years 5 months ago
Time series shapelets: a new primitive for data mining
Classification of time series has been attracting great interest over the past decade. Recent empirical evidence has strongly suggested that the simple nearest neighbor algorithm ...
Lexiang Ye, Eamonn J. Keogh
ICDE
2009
IEEE
173views Database» more  ICDE 2009»
14 years 7 months ago
Efficient Processing of Warping Time Series Join of Motion Capture Data
Discovering non-trivial matching subsequences from two time series is very useful in synthesizing novel time series. This can be applied to applications such as motion synthesis wh...
Yueguo Chen, Gang Chen, Ke Chen, Beng Chin Ooi
SDM
2009
SIAM
164views Data Mining» more  SDM 2009»
14 years 2 months ago
Exact Discovery of Time Series Motifs.
Time series motifs are pairs of individual time series, or subsequences of a longer time series, which are very similar to each other. As with their discrete analogues in computat...
Abdullah Mueen, Eamonn J. Keogh, M. Brandon Westov...
KDD
2003
ACM
194views Data Mining» more  KDD 2003»
14 years 5 months ago
Finding recent frequent itemsets adaptively over online data streams
A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is more likely to be c...
Joong Hyuk Chang, Won Suk Lee
CLUSTER
2002
IEEE
13 years 5 months ago
Online Prediction of the Running Time of Tasks
Abstract. We describe and evaluate the Running Time Advisor (RTA), a system that can predict the running time of a compute-bound task on a typical shared, unreserved commodity host...
Peter A. Dinda