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WSOM
2009
Springer
13 years 11 months ago
Incremental Unsupervised Time Series Analysis Using Merge Growing Neural Gas
We propose Merge Growing Neural Gas (MGNG) as a novel unsupervised growing neural network for time series analysis. MGNG combines the state-of-the-art recursive temporal context of...
Andreas Andreakis, Nicolai von Hoyningen-Huene, Mi...
IV
2009
IEEE
131views Visualization» more  IV 2009»
13 years 11 months ago
A Visualization and Level-of-Detail Control Technique for Large Scale Time Series Data
We have various interesting time series data in our daily life, such as weather data (e.g., temperature and air pressure) and stock prices. Polyline chart is one of the most commo...
Yumiko Uchida, Takayuki Itoh
INFOCOM
2009
IEEE
13 years 11 months ago
Measuring Complexity and Predictability in Networks with Multiscale Entropy Analysis
—We propose to use multiscale entropy analysis in characterisation of network traffic and spectrum usage. We show that with such analysis one can quantify complexity and predict...
Janne Riihijärvi, Matthias Wellens, Petri M&a...
ICDM
2009
IEEE
121views Data Mining» more  ICDM 2009»
13 years 11 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...
CEC
2009
IEEE
13 years 11 months ago
Mining an optimal prototype from a periodic time series: An evolutionary computation-based approach
— The mining of meaningful shapes of time series is done widely in order to find shapes that can be used, for example, in classification problems or in summarizing signals. Nor...
Pekka Siirtola, Perttu Laurinen, Juha Röning
DASFAA
2009
IEEE
118views Database» more  DASFAA 2009»
13 years 11 months ago
Periodic Pattern Analysis in Time Series Databases
Similarity search in time series data is used in diverse domains. The most prominent work has focused on similarity search considering either complete time series or certain subseq...
Johannes Aßfalg, Thomas Bernecker, Hans-Pete...

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flylianPostdoctoral
HKUST
flylian
EDBT
2006
ACM
122views Database» more  EDBT 2006»
14 years 5 months ago
TQuEST: Threshold Query Execution for Large Sets of Time Series
Effective and efficient data mining in time series databases is essential in many application domains as for instance in financial analysis, medicine, meteorology, and environmenta...
Johannes Aßfalg, Hans-Peter Kriegel, Peer Kr...
EDBT
2006
ACM
120views Database» more  EDBT 2006»
14 years 5 months ago
Similarity Search on Time Series Based on Threshold Queries
Similarity search in time series data is required in many application fields. The most prominent work has focused on similarity search considering either complete time series or si...
Johannes Aßfalg, Hans-Peter Kriegel, Peer Kr...
KDD
2002
ACM
182views Data Mining» more  KDD 2002»
14 years 5 months ago
On the need for time series data mining benchmarks: a survey and empirical demonstration
In the last decade there has been an explosion of interest in mining time series data. Literally hundreds of papers have introduced new algorithms to index, classify, cluster and s...
Eamonn J. Keogh, Shruti Kasetty