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Resource-aware kernel density estimators over streaming data
2006
Proceedings of the 15th ACM international conference on Information and knowledge management - CIKM '06
A variety of real-world applications heavily relies on the analysis of transient data streams. Due to the rigid processing requirements of data streams, common analysis techniques as known from data mining are not applicable. A fundamental building block of many data mining and analysis approaches is density estimation. It provides a well-defined estimation of a continuous data distribution, a fact which makes its adaptation to data streams desirable. A convenient method for density estimation
doi:10.1145/1183614.1183772
dblp:conf/cikm/HeinzS06
fatcat:kose47v4jfbdtghincdne7obka