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KDD
2004
ACM
210views Data Mining» more  KDD 2004»
15 years 10 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...
VLDB
2005
ACM
196views Database» more  VLDB 2005»
15 years 3 months ago
Summarizing and Mining Inverse Distributions on Data Streams via Dynamic Inverse Sampling
Emerging data stream management systems approach the challenge of massive data distributions which arrive at high speeds while there is only small storage by summarizing and minin...
Graham Cormode, S. Muthukrishnan, Irina Rozenbaum
PAKDD
2007
ACM
144views Data Mining» more  PAKDD 2007»
15 years 3 months ago
Approximately Mining Recently Representative Patterns on Data Streams
Catching the recent trend of data is an important issue when mining frequent itemsets from data streams. To prevent from storing the whole transaction data within the sliding windo...
Jia-Ling Koh, Yuan-Bin Don
ICPR
2008
IEEE
15 years 4 months ago
An online polygonal approximation of digital signals and curves with Dynamic Programming algorithm
A fast online algorithm was developed for polygonal approximation of signals and curves with a minimum number of line segments for a given constraint on the standard deviation of ...
Alexander Kolesnikov
PODS
2006
ACM
122views Database» more  PODS 2006»
15 years 9 months ago
Space- and time-efficient deterministic algorithms for biased quantiles over data streams
Skew is prevalent in data streams, and should be taken into account by algorithms that analyze the data. The problem of finding "biased quantiles"-- that is, approximate...
Graham Cormode, Flip Korn, S. Muthukrishnan, Dives...