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» Fast mining of complex time-stamped events
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CIKM
2008
Springer
13 years 6 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, ...
KDD
2012
ACM
221views Data Mining» more  KDD 2012»
11 years 7 months ago
Fast mining and forecasting of complex time-stamped events
Given huge collections of time-evolving events such as web-click logs, which consist of multiple attributes (e.g., URL, userID, timestamp), how do we find patterns and trends? Ho...
Yasuko Matsubara, Yasushi Sakurai, Christos Falout...
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
14 years 5 months ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
ICDE
2011
IEEE
235views Database» more  ICDE 2011»
12 years 8 months ago
Fast data analytics with FPGAs
—The rapidly increasing amount of data available for real-time analysis (i.e., so-called operational business intelligence) is creating an interesting opportunity for creative ap...
Louis Woods, Gustavo Alonso
SDM
2010
SIAM
256views Data Mining» more  SDM 2010»
13 years 6 months ago
The Application of Statistical Relational Learning to a Database of Criminal and Terrorist Activity
We apply statistical relational learning to a database of criminal and terrorist activity to predict attributes and event outcomes. The database stems from a collection of news ar...
B. Delaney, Andrew S. Fast, W. M. Campbell, C. J. ...