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ICDM
2005
IEEE
189views Data Mining» more  ICDM 2005»
14 years 3 months ago
Integrating Hidden Markov Models and Spectral Analysis for Sensory Time Series Clustering
We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to da...
Jie Yin, Qiang Yang
PKDD
2001
Springer
185views Data Mining» more  PKDD 2001»
14 years 2 months ago
Temporal Rule Discovery for Time-Series Satellite Images and Integration with RDB
Feature extraction and knowledge discovery from a large amount of image data such as remote sensing images have become highly required recent years. In this study, a framework for ...
Rie Honda, Osamu Konishi
KDD
2003
ACM
146views Data Mining» more  KDD 2003»
14 years 10 months ago
Probabilistic discovery of time series motifs
Several important time series data mining problems reduce to the core task of finding approximately repeated subsequences in a longer time series. In an earlier work, we formalize...
Bill Yuan-chi Chiu, Eamonn J. Keogh, Stefano Lonar...
ECML
1997
Springer
14 years 1 months ago
Parallel and Distributed Search for Structure in Multivariate Time Series
Abstract. E cient data mining algorithms are crucial fore ective knowledge discovery. We present the Multi-Stream Dependency Detection (msdd) data mining algorithm that performs a ...
Tim Oates, Matthew D. Schmill, Paul R. Cohen
ICDM
2009
IEEE
121views Data Mining» more  ICDM 2009»
14 years 4 months ago
Finding Time Series Motifs in Disk-Resident Data
—Time series motifs are sets of very similar subsequences of a long time series. They are of interest in their own right, and are also used as inputs in several higher-level data...
Abdullah Mueen, Eamonn J. Keogh, Nima Bigdely Sham...