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ICDM
2003
IEEE
240views Data Mining» more  ICDM 2003»
15 years 7 months ago
Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research
Given the recent explosion of interest in streaming data and online algorithms, clustering of time series subsequences, extracted via a sliding window, has received much attention...
Eamonn J. Keogh, Jessica Lin, Wagner Truppel
SDM
2007
SIAM
137views Data Mining» more  SDM 2007»
15 years 3 months ago
Are approximation algorithms for consensus clustering worthwhile?
Consensus clustering has emerged as one of the principal clustering problems in the data mining community. In recent years the theoretical computer science community has generated...
Michael Bertolacci, Anthony Wirth
ICDM
2003
IEEE
130views Data Mining» more  ICDM 2003»
15 years 7 months ago
Information Theoretic Clustering of Sparse Co-Occurrence Data
A novel approach to clustering co-occurrence data poses it as an optimization problem in information theory which minimizes the resulting loss in mutual information. A divisive cl...
Inderjit S. Dhillon, Yuqiang Guan
KDD
1997
ACM
72views Data Mining» more  KDD 1997»
15 years 5 months ago
Detecting Atmospheric Regimes Using Cross-Validated Clustering
Low-frequency variability in geopotential height records of the Northern Hemisphere is a topic of significance in atmospheric science, having profound implications for climate mod...
Padhraic Smyth, Michael Ghil, Kayo Ide, Joseph Rod...
SDM
2008
SIAM
177views Data Mining» more  SDM 2008»
15 years 3 months ago
Robust Clustering in Arbitrarily Oriented Subspaces
In this paper, we propose an efficient and effective method to find arbitrarily oriented subspace clusters by mapping the data space to a parameter space defining the set of possi...
Elke Achtert, Christian Böhm, Jörn David...