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» On the Complexity of Mining Temporal Trends
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KDD
2009
ACM
172views Data Mining» more  KDD 2009»
15 years 4 months ago
Learning dynamic temporal graphs for oil-production equipment monitoring system
Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
Yan Liu, Jayant R. Kalagnanam, Oivind Johnsen
CIKM
2008
Springer
15 years 1 months ago
Fast mining of complex time-stamped events
Given a collection of complex, time-stamped events, how do we find patterns and anomalies? Events could be meetings with one or more persons with one or more agenda items at zero ...
Hanghang Tong, Yasushi Sakurai, Tina Eliassi-Rad, ...
DAWAK
2003
Springer
15 years 4 months ago
Automatic Detection of Structural Changes in Data Warehouses
Data Warehouses provide sophisticated tools for analyzing complex data online, in particular by aggregating data along dimensions spanned by master data. Changes to these master da...
Johann Eder, Christian Koncilia, Dieter Mitsche
WSDM
2012
ACM
301views Data Mining» more  WSDM 2012»
13 years 7 months ago
Learning evolving and emerging topics in social media: a dynamic nmf approach with temporal regularization
As massive repositories of real-time human commentary, social media platforms have arguably evolved far beyond passive facilitation of online social interactions. Rapid analysis o...
Ankan Saha, Vikas Sindhwani
KDD
2007
ACM
168views Data Mining» more  KDD 2007»
16 years 2 days ago
Finding tribes: identifying close-knit individuals from employment patterns
We present a family of algorithms to uncover tribes--groups of individuals who share unusual sequences of affiliations. While much work inferring community structure describes lar...
Lisa Friedland, David Jensen