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» Detecting Anomalies and Intruders
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KDD
2008
ACM
165views Data Mining» more  KDD 2008»
14 years 7 months ago
Colibri: fast mining of large static and dynamic graphs
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Hanghang Tong, Spiros Papadimitriou, Jimeng Sun, P...
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
14 years 7 months ago
Cleaning disguised missing data: a heuristic approach
In some applications such as filling in a customer information form on the web, some missing values may not be explicitly represented as such, but instead appear as potentially va...
Ming Hua, Jian Pei
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 7 months ago
Visually mining and monitoring massive time series
Moments before the launch of every space vehicle, engineering discipline specialists must make a critical go/no-go decision. The cost of a false positive, allowing a launch in spi...
Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Jef...
SIGMOD
2006
ACM
171views Database» more  SIGMOD 2006»
14 years 7 months ago
Communication-efficient distributed monitoring of thresholded counts
Monitoring is an issue of primary concern in current and next generation networked systems. For example, the objective of sensor networks is to monitor their surroundings for a va...
Ram Keralapura, Graham Cormode, Jeyashankher Ramam...
PODS
2007
ACM
225views Database» more  PODS 2007»
14 years 7 months ago
Sketching unaggregated data streams for subpopulation-size queries
IP packet streams consist of multiple interleaving IP flows. Statistical summaries of these streams, collected for different measurement periods, are used for characterization of ...
Edith Cohen, Nick G. Duffield, Haim Kaplan, Carste...