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» Discovering Temporal Knowledge in Multivariate Time Series
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VLDB
1998
ACM
142views Database» more  VLDB 1998»
13 years 11 months ago
On the Discovery of Interesting Patterns in Association Rules
Many decision support systems, which utilize association rules for discovering interesting patterns, require the discovery of association rules that vary over time. Such rules des...
Sridhar Ramaswamy, Sameer Mahajan, Abraham Silbers...
ICML
2006
IEEE
14 years 8 months ago
Hidden process models
We introduce Hidden Process Models (HPMs), a class of probabilistic models for multivariate time series data. The design of HPMs has been motivated by the challenges of modeling h...
Rebecca Hutchinson, Tom M. Mitchell, Indrayana Rus...
ICDM
2010
IEEE
99views Data Mining» more  ICDM 2010»
13 years 5 months ago
A System for Mining Temporal Physiological Data Streams for Advanced Prognostic Decision Support
We present a mining system that can predict the future health status of the patient using the temporal trajectories of health status of a set of similar patients. The main noveltie...
Jimeng Sun, Daby Sow, Jianying Hu, Shahram Ebadoll...
WSDM
2012
ACM
325views Data Mining» more  WSDM 2012»
12 years 3 months ago
Coupled temporal scoping of relational facts
Recent research has made significant advances in automatically constructing knowledge bases by extracting relational facts (e.g., Bill Clinton-presidentOf-US) from large text cor...
Partha Pratim Talukdar, Derry Tanti Wijaya, Tom Mi...
SDM
2009
SIAM
170views Data Mining» more  SDM 2009»
14 years 4 months ago
Mining Complex Spatio-Temporal Sequence Patterns.
Mining sequential movement patterns describing group behaviour in potentially streaming spatio-temporal data sets is a challenging problem. Movements are typically noisy and often...
Florian Verhein