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CIDM
2007
IEEE
14 years 2 months ago
Incremental Local Outlier Detection for Data Streams
Outlier detection has recently become an important problem in many industrial and financial applications. This problem is further complicated by the fact that in many cases, outlie...
Dragoljub Pokrajac, Aleksandar Lazarevic, Longin J...
ICDM
2010
IEEE
115views Data Mining» more  ICDM 2010»
13 years 6 months ago
Polishing the Right Apple: Anytime Classification Also Benefits Data Streams with Constant Arrival Times
Classification of items taken from data streams requires algorithms that operate in time sensitive and computationally constrained environments. Often, the available time for class...
Jin Shieh, Eamonn J. Keogh
KDD
2006
ACM
129views Data Mining» more  KDD 2006»
14 years 8 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
CN
2006
163views more  CN 2006»
13 years 8 months ago
A framework for mining evolving trends in Web data streams using dynamic learning and retrospective validation
The expanding and dynamic nature of the Web poses enormous challenges to most data mining techniques that try to extract patterns from Web data, such as Web usage and Web content....
Olfa Nasraoui, Carlos Rojas, Cesar Cardona
ICDE
2008
IEEE
139views Database» more  ICDE 2008»
14 years 9 months ago
Simultaneous Equation Systems for Query Processing on Continuous-Time Data Streams
We introduce Pulse, a framework for processing continuous queries over models of continuous-time data, which can compactly and accurately represent many real-world activities and p...
Jennie Rogers, Olga Papaemmanouil, Ugur Çet...