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Moreover, the work shows that the approach is computationally efficient, even for large data and keyword sets.
The research results provide research basis to better design a clustering partition algorithm in large data and high efficiency.
For analyzing large data and mining Big Data MapReduce framework is used in a number of works.
The advantages of the clustering are that it can deal with large data and create groups without requiring training data.
If you have large data and storage requirements, you need someone who knows his or her way around, say, Amazon.com's S3 storage service.
Big crisis data incorporates both very large data and also a large number of sources of data (that may be providing diverse kinds of data).
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The age data were missing for many observations and were not included in model comparisons in order to use larger data and to avoid overparameterization.
This procedure is well suited to large data sets and combinations of categorical and continuous variables.
Yes, and applications that rely on large data sets and small bandwidth are well suited to cloud computing.
Delay-insensitive applications with large data transfer and web browsing are grouped under nrtPS and BE service class, respectively.
The tiling and cutoff techniques are used to process large data sets and avoid memory bandwidth limitations [ 31, 32].
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