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» Finding frequent items in data streams
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PODS
2009
ACM
100views Database» more  PODS 2009»
14 years 8 months ago
Space-optimal heavy hitters with strong error bounds
The problem of finding heavy hitters and approximating the frequencies of items is at the heart of many problems in data stream analysis. It has been observed that several propose...
Radu Berinde, Graham Cormode, Piotr Indyk, Martin ...
CORR
2008
Springer
99views Education» more  CORR 2008»
13 years 7 months ago
A Model-Based Frequency Constraint for Mining Associations from Transaction Data
Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an associatio...
Michael Hahsler
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
14 years 8 months ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...
BMCBI
2006
114views more  BMCBI 2006»
13 years 7 months ago
Mining frequent patterns for AMP-activated protein kinase regulation on skeletal muscle
Background: AMP-activated protein kinase (AMPK) has emerged as a significant signaling intermediary that regulates metabolisms in response to energy demand and supply. An investig...
Qingfeng Chen, Yi-Ping Phoebe Chen
ICML
1996
IEEE
14 years 8 months ago
Searching for Structure in Multiple Streams of Data
Finding structure in multiple streams of data is an important problem. Consider the streams of data owing from a robot's sensors, the monitors in an intensive care unit, or p...
Tim Oates, Paul R. Cohen