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» Quantizing Time Series for Efficient Subsequence Matching
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KDD
1997
ACM
213views Data Mining» more  KDD 1997»
14 years 1 days ago
A Probabilistic Approach to Fast Pattern Matching in Time Series Databases
Theproblemof efficiently and accurately locating patterns of interest in massivetimeseries data sets is an important and non-trivial problemin a wide variety of applications, incl...
Eamonn J. Keogh, Padhraic Smyth
SIGMOD
2007
ACM
186views Database» more  SIGMOD 2007»
14 years 8 months ago
An efficient and accurate method for evaluating time series similarity
A variety of techniques currently exist for measuring the similarity between time series datasets. Of these techniques, the methods whose matching criteria is bounded by a specifi...
Michael D. Morse, Jignesh M. Patel
DMIN
2006
122views Data Mining» more  DMIN 2006»
13 years 9 months ago
Clustering of Bi-Dimensional and Heterogeneous Time Series: Application to Social Sciences Data
We present an application of bi-dimensional and heterogeneous time series clustering in order to resolve a Social Sciences issue. The dataset is the result of a survey involving mo...
Rémi Gaudin, Sylvaine Barbier, Nicolas Nico...
TCS
2008
13 years 7 months ago
Algorithms for computing variants of the longest common subsequence problem
The longest common subsequence(LCS) problem is one of the classical and wellstudied problems in computer science. The computation of the LCS is a frequent task in DNA sequence ana...
Costas S. Iliopoulos, M. Sohel Rahman
KDD
2010
ACM
199views Data Mining» more  KDD 2010»
13 years 11 months ago
Online discovery and maintenance of time series motifs
The detection of repeated subsequences, time series motifs, is a problem which has been shown to have great utility for several higher-level data mining algorithms, including clas...
Abdullah Mueen, Eamonn J. Keogh