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Exact(27)
Applying principal component analysis reduces the data complexity while preserving sufficient data variance.
The data complexity of eDatalog(^lnot ) with respect to the well-founded semantics is in PTime.
The data complexity of WORL with respect to the well-founded semantics is in PTime.
As a consequence, the data complexity of SWORL w.r.t. the standard semantics is in PTime.
The data complexity of SWORL with respect to the standard semantics is in PTime.
As a consequence, the data complexity of stratified eDatalog(^lnot ) with respect to the standard semantics is in PTime.
Similar(32)
Experiments show that the QKLMS-MDL successfully adjusts the network size according to the input data complexity while keeping the accuracy in an acceptable range.
Keeping in view the big data complexity, the need for big data reduction, and analyzing big data reduction problem in different perspective, we present a thorough literature review of the methods for big data reduction.
In this way, the authors [11] applied corsets to reduce the big data into small and manageable size, which reduces the overall data complexity.
Therefore, the relevant reduction methods and systems should be designed to handle the big data complexity at all stages of big data processing.
The extensive literature review exhibits that the big data reduction methods and systems have potential to deal with the big data complexity at both algorithms and systems level.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com