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Approximation Trade-Offs in Markovian Stream Processing: An Empirical Study

10 years 1 months ago
Approximation Trade-Offs in Markovian Stream Processing: An Empirical Study
Abstract-- A large amount of the world's data is both sequential and imprecise. Such data is commonly modeled as Markovian streams; examples include words/sentences inferred from raw audio signals, or discrete location sequences inferred from RFID or GPS data. The rich semantics and large volumes of these streams make them difficult to query efficiently. In this paper, we study the effects--on both efficiency and accuracy--of two common stream approximations. Through experiments on a realworld RFID data set, we identify conditions under which these approximations can improve performance by several orders of magnitude, with only minimal effects on query results. We also identify cases when the full rich semantics are necessary.
Julie Letchner, Christopher Re, Magdalena Balazins
Added 20 Dec 2009
Updated 03 Jan 2010
Type Conference
Year 2010
Where ICDE
Authors Julie Letchner, Christopher Re, Magdalena Balazinska, Matthai Philipose
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