Conditional Heavy Hitters: Detecting Interesting Correlations in Data Streams. Katsiaryna Mirylenka · Graham Cormode · Themis Palpanas · Divesh Srivastava.
Conditional heavy hitters: detecting interesting correlations in data ...
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Feb 26, 2015 · We develop and describe several streaming algorithms for retrieving conditional heavy hitters, and we analyze their applicability for data with ...
We introduce several algorithm variations that allow us to efficiently find conditional heavy hitters for input data with very different characteristics, and ...
Abstract The notion of heavy hitters—items that make up a large fraction of the population—has been success- fully used in a variety of applications across ...
We introduce several algorithm variations that allow us to efficiently find conditional heavy hitters for input data with very different characteristics, and ...
Feb 26, 2015 · We introduce several algorithm variations that allow us to efficiently find conditional heavy hitters for input data with very different ...
to find conditional heavy hitters from a stream of data. Our experimental results are shown in Section V, and we conclude our discussion in Section VI. II ...
This work introduces and formalizes the notion of Conditional Heavy Hitters to identify such items, with applications in network monitoring, ...
We introduce several streaming algorithms that allow us to find conditional heavy hitters efficiently, and provide analytical results. Different algorithms are ...
We introduce several streaming algorithms that allow us to find conditional heavy hitters efficiently, and provide analytical results. Different algorithms are ...