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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...
TKDE
2010
150views more  TKDE 2010»
14 years 7 months ago
Prospective Infectious Disease Outbreak Detection Using Markov Switching Models
—Accurate and timely detection of infectious disease outbreaks provides valuable information which can enable public health officials to respond to major public health threats in...
Hsin-Min Lu, Daniel Zeng, Hsinchun Chen
BMCBI
2008
142views more  BMCBI 2008»
14 years 9 months ago
Identification of biomarkers for genotyping Aspergilli using non-linear methods for clustering and classification
Background: In the present investigation, we have used an exhaustive metabolite profiling approach to search for biomarkers in recombinant Aspergillus nidulans (mutants that produ...
Irene Kouskoumvekaki, Zhiyong Yang, Svava Ó...
KDD
2009
ACM
364views Data Mining» more  KDD 2009»
15 years 10 months ago
Causality quantification and its applications: structuring and modeling of multivariate time series
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
Takashi Shibuya, Tatsuya Harada, Yasuo Kuniyoshi
73
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ICDM
2008
IEEE
123views Data Mining» more  ICDM 2008»
15 years 3 months ago
Discovering Flow Anomalies: A SWEET Approach
Given a percentage-threshold and readings from a pair of consecutive upstream and downstream sensors, flow anomaly discovery identifies dominant time intervals where the fractio...
James M. Kang, Shashi Shekhar, Christine Wennen, P...