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ICDM
2009
IEEE
122views Data Mining» more  ICDM 2009»
15 years 6 months ago
Detecting and Interpreting Variable Interactions in Observational Ornithology Data
In this paper we demonstrate a practical approach to interaction detection on real data describing the abundance of different species of birds in the prairies east of the souther...
Daria Sorokina, Rich Caruana, Mirek Riedewald, Wes...
INFOCOM
2011
IEEE
14 years 3 months ago
Reconciling privacy preservation and intrusion detection in sensory data aggregation
—When wireless sensors are deployed to monitor the working or life conditions of people, the data collected and processed by these sensors may reveal privacy of people. The actua...
Chuang Wang, Guiling Wang, Wensheng Zhang 0001, Ta...
EUROPAR
2004
Springer
15 years 5 months ago
Detecting Data Races in Sequential Programs with DIOTA
In this paper we show that data races, a type of bug that generally only causes havoc in parallel programs, can also occur in sequential programs that use signal handlers. Fortunat...
Michiel Ronsse, Jonas Maebe, Koenraad De Bosschere
IDA
2007
Springer
14 years 11 months ago
Anomaly detection in data represented as graphs
An important area of data mining is anomaly detection, particularly for fraud. However, little work has been done in terms of detecting anomalies in data that is represented as a g...
William Eberle, Lawrence B. Holder
ACSAC
2004
IEEE
15 years 3 months ago
RACOON: Rapidly Generating User Command Data For Anomaly Detection From Customizable Templates
One of the biggest obstacles faced by user command based anomaly detection techniques is the paucity of data. Gathering command data is a slow process often spanning months or yea...
Ramkumar Chinchani, Aarthie Muthukrishnan, Madhusu...