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AAAI
2007
14 years 11 months ago
Discovering Multivariate Motifs using Subsequence Density Estimation and Greedy Mixture Learning
The problem of locating motifs in real-valued, multivariate time series data involves the discovery of sets of recurring patterns embedded in the time series. Each set is composed...
David Minnen, Charles Lee Isbell Jr., Irfan A. Ess...
SDM
2009
SIAM
130views Data Mining» more  SDM 2009»
15 years 6 months ago
FuncICA for Time Series Pattern Discovery.
We introduce FuncICA, a new independent component analysis method for pattern discovery in inherently functional data, such as time series data. FuncICA can be considered an analo...
Alexander Gray, Nishant Mehta
ADC
2007
Springer
140views Database» more  ADC 2007»
15 years 3 months ago
Incremental Mining for Temporal Association Rules for Crime Pattern Discoveries
In recent years, the concept of temporal association rule (TAR) has been introduced in order to solve the problem on handling time series by including time expressions into associ...
Vincent T. Y. Ng, Stephen Chi-fai Chan, Derek Lau,...
JIIS
2006
113views more  JIIS 2006»
14 years 9 months ago
Spatial ordering and encoding for geographic data mining and visualization
: Geographic information (e.g., locations, networks, and nearest neighbors) are unique and different from other aspatial attributes (e.g., population, sales, or income). It is a ch...
Diansheng Guo, Mark Gahegan
CGF
2011
14 years 1 months ago
Visual Exploration of Time-Series Data with Shape Space Projections
Time-series data is a common target for visual analytics, as they appear in a wide range of application domains. Typical tasks in analyzing time-series data include identifying cy...
Matthew O. Ward, Zhenyu Guo